Principal Product Manager (Agentic Platform)

🏢 Summary: Senior hands-on Staff Data Engineer role focused on owning and scaling a centralized Databricks lakehouse platform, building production-grade data pipelines, and leading multi-terabyte legacy migrations. The position combines architectural decision-making, data modeling, and technical leadership to support multiple financial product lines. The engineer acts as the primary onshore technical authority ensuring platform reliability, governance, and scalability. 🗂️ Requirements: 5+ years of data engineering experience, Strong proficiency in SQL, Python, and PySpark, Hands-on experience with Databricks (Delta Lake, Workflows, Databricks SQL), Experience building and maintaining large-scale ETL/ELT pipelines, Proven ability to design scalable data models, Experience migrating multi-terabyte datasets, AWS experience (S3, IAM, VPC), Infrastructure-as-code experience (Terraform preferred), Knowledge of data governance, lineage, and access controls, Ability to make independent architectural decisions, Experience mentoring data engineers, US-based with timezone overlap for stakeholder collaboration 📃 Skills: SQL, Python, PySpark, Databricks, Delta, Lake, Workflows, DatabricksSQL, UnityCatalog, AWS, S3, IAM, VPC, Terraform, ETL, ELT, DataModeling, Governance 🏢 Description: Exactera has offices in New York City, Tarrytown NY, San Diego, CA, London, and Argentina. The Role As Staff Data Engineer, you will provide senior onshore technical leadership for the data engineering team. You will own a defined slice of our centralized Databricks data platform with full accountability for decisions and delivery, serve as a technical counterpart to the Principal Data Platform Engineer, and drive architectural judgment and independent problem-solving as platform complexity scales post-migration. This is a hands-on data engineering role focused on building and maintaining production pipelines, exercising architectural judgment on data modeling and pipeline design, and serving as the onshore escalation point and institutional knowledge backup for platform decisions. The Business Challenge We operate multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning), each with distinct databases containing enterprise financial data—journal entries, general ledgers, and financial statements. Our immediate challenge is migrating multi-terabyte datasets from legacy systems to a unified Databricks lakehouse while establishing governance patterns that enable multi-product operations at scale. As the platform matures, the data engineering team needs senior onshore technical presence to drive architecture ownership and maintain platform quality. What You'll Build Production Data Pipelines: Build and maintain production data pipelines within the patterns and governance established by the Lead Data Platform Engineer, ensuring reliability and performance at multi-terabyte scale. Data Modeling & Architecture: Exercise architectural judgment on data modeling, pipeline design, and platform usage—translating complex business requirements into scalable data solutions across our product portfolio. Stakeholder Engagement: Engage proactively with product and engineering stakeholders to translate requirements into data solutions, serving as the primary onshore technical point of contact for data engineering needs. Platform Quality: Drive platform quality through code reviews, testing practices, and engineering standards that ensure the team delivers reliable, maintainable data infrastructure. Knowledge & Continuity: Serve as onshore escalation point and institutional knowledge backup for platform decisions, reducing single-point-of-failure risk and building onshore technical depth as the platform scales. Business Problems You'll Solve Multi-Product Data Delivery: Implement data pipelines that serve multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning) with distinct data requirements, ensuring each product gets the data it needs reliably and on schedule. Legacy Migration Execution: Lead pipeline implementation for migrating multi-terabyte datasets from legacy systems to Databricks, working within the architecture defined by the Lead Data Platform Engineer. Onshore Technical Leadership: Provide the senior judgment layer the current nearshore team cannot—owning problems end-to-end, making independent architectural decisions, and mentoring engineers to raise the quality bar across the team. Cross-Team Coordination: Bridge the gap between product teams and data infrastructure, translating business requirements into data solutions and ensuring the data platform delivers on product commitments. Required Experience Core Data Engineering SQL, Python, and PySpark—production pipeline implementation and performance optimization Databricks experience—Delta Lake, Workflows, and Databricks SQL; Unity Catalog familiarity preferred 5+ years in data engineering with demonstrated ability to own problems end-to-end without close direction Experience building and maintaining ETL/ELT pipelines at scale, including error handling, monitoring, and data quality validation Strong data modeling skills across structured and semi-structured data sources Platform & Infrastructure AWS experience (S3, IAM, VPC) with ability to collaborate on infrastructure decisions Infrastructure-as-code experience (Terraform preferred) Familiarity with data governance patterns (Unity Catalog, data lineage, access controls) Technical Leadership Demonstrated ability to exercise independent architectural judgment—not just ticket execution Experience mentoring or guiding junior and mid-level data engineers Strong written and verbal communication—able to document architecture decisions and engage directly with both technical and business stakeholders Onshore (US-based)—role requires timezone overlap, async-light communication, and direct stakeholder engagement Preferred But Not Required Experience with financial data, accounting systems (NetSuite), or enterprise ERP platforms Background building pipelines that serve AI/ML workloads (preparing data for downstream ML consumption, RAG, and LLMs) Familiarity with data governance frameworks and compliance requirements for regulated industries Experience working alongside or transitioning from nearshore engineering teams What We Offer (The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. We are committed to diversity, inclusion, and equal opportunities for all. What We Offer:(The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us: At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. With over $100 million in funding from Savant Venture Fund and Insight Partners, we are poised for growth. We are committed to diversity, inclusion, and equal opportunities for all.

🏢 Summary: Principal Data Platform Engineer role focused on architecting and implementing a centralized Databricks lakehouse platform, including governance, ETL frameworks, and large-scale data migration. The position centers on building scalable, cost-efficient, and well-governed data infrastructure across multiple product lines. It involves leading multi-terabyte legacy migrations and establishing robust platform operations for analytics and AI workloads. 🗂️ Requirements: 5-8 years in data engineering or data platform roles, 3+ years hands-on experience with Databricks, Production experience with Unity Catalog and multi-catalog governance, Expert experience with Delta Lake optimization at multi-TB scale, Strong hands-on experience with Delta Live Tables, Experience with Databricks Workflows for orchestration and monitoring, Strong proficiency in PySpark and Databricks SQL, Experience designing unified schemas across disparate data sources, AWS experience including S3, IAM, VPC, Infrastructure-as-code experience (Terraform preferred), Experience leading at least one significant platform build or migration project, Ability to architect data platforms and document technical decisions 📃 Skills: Databricks, UnityCatalog, DeltaLake, DeltaLiveTables, PySpark, DatabricksSQL, AWS, S3, IAM, VPC, Terraform, SQL, ETL, Z-ordering, Compaction, Clustering 🏢 Description: Exactera has offices in New York City, Tarrytown NY, San Diego, CA, London, and Argentina. The Role As Principal Data Platform Engineer, you'll architect and implement our centralized data platform on Databricks. You'll establish governance patterns using Unity Catalog, optimize for cost and performance at scale, and enable our existing Data Engineers to build confidently on the platform. This is a data infrastructure role—focused on pipelines, storage, governance, and platform operations. The Business Challenge We operate multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning), each with distinct databases containing enterprise financial data—journal entries, general ledgers, and financial statements. Our immediate challenge is migrating multi-terabyte datasets from legacy systems to a unified Databricks lakehouse while establishing governance patterns that enable multi-product operations at scale. What You'll Build Data Structuring: Design data models and implement unified schemas across multiple disparate product lines. Unity Catalog Architecture: Design and implement multi-catalog governance strategy supporting data isolation, cross-product data sharing, and comprehensive lineage tracking across our product portfolio Delta Lake Optimization: Establish patterns for Z-ordering, compaction, and liquid clustering at multi-TB scale. Define table structures, partitioning strategies, and retention policies that balance query performance with storage costs ETL Pipeline Framework: Build declarative pipeline patterns using Delta Live Tables. Create orchestration workflows for ingesting data from internal sources such as SQL databases and S3 Third Party Integrations: Integrate with third party data sources such as ERP systems (Netsuite etc.) and external data providers (S&P etc.) with automated ingest, robust error handling and monitoring. Platform Operations: Implement cost monitoring and optimization strategies, establish data quality frameworks, create self-service patterns enabling Data Engineers to work independently while maintaining governance standards Business Problems You'll Solve Key Legacy Product Migrations: Lead the architecture for migrating multi-terabyte datasets from legacy systems to Databricks—establishing patterns that will be reused across multiple product lines Multi-Product Data Architecture: Design Unity Catalog structures enabling secure data separation between product lines while allowing controlled cross-product analytics where appropriate Cost-Efficient Scale: Build infrastructure that scales efficiently—through intelligent caching, query optimization, and compute management strategies that avoid linear cost growth Platform Reliability: Establish monitoring, alerting, and data quality validation ensuring the platform operates reliably as foundation for both analytics and AI workloads Required Experience Databricks Expertise (Required) Unity Catalog: Production experience with multi-catalog governance, metastore design, and lineage tracking. Data Structuring: Experience designing and building unified schemas across multiple disparate product lines. Delta Lake: Expert-level experience with Z-ordering, compaction, liquid clustering, and performance tuning at multi-TB scale Delta Live Tables: Strong hands-on experience building declarative ETL pipelines, including change data capture and expectations/constraints Databricks Workflows: Experience with job orchestration, scheduling, and operational monitoring Business Intelligence: Experience enabling company-wide analytics and reporting with modern business intelligence tools and maintaining source of truth data and metrics. PySpark & Databricks SQL: Strong proficiency for code review, performance tuning, and query optimization Core Platform Engineering 5-8 years in data engineering or data platform roles, with 3+ years hands-on Databricks experience Track record leading at least one significant platform build or migration project AWS experience (S3, IAM, VPC) with ability to collaborate on infrastructure decisions Infrastructure-as-code experience (Terraform preferred) Technical Leadership Demonstrated ability architecting data platforms from first principles and defending technical decisions Strong written and verbal communication— document architecture decisions and present to both technical and business stakeholders Preferred But Not Required Experience with financial data, accounting systems (NetSuite), or enterprise ERP platforms Background building platforms that serve AI/ML workloads (experience preparing data for downstream ML consumption, RAG and retrieval, and LLMs. Understand advanced intelligence concepts such as relationship surfacing with knowledge graphs Familiarity with data governance frameworks and compliance requirements for regulated industries What We Offer:(The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us: At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. With over $100 million in funding from Savant Venture Fund and Insight Partners, we are poised for growth. We are committed to diversity, inclusion, and equal opportunities for all.

🏢 Summary: Senior AI-native full-stack engineer role focused on building and owning production-grade agentic systems end-to-end, from architecture to deployment and on-call. The position involves developing multi-agent workflows, RAG pipelines, and AI infrastructure, as well as delivering client-facing B2B solutions on top of an internal agent platform. Strong ownership, hands-on LLM production experience, and full-stack execution across frontend, backend, and cloud infrastructure are required. 🗂️ Requirements: 5+ years of production software engineering experience, 1-2+ years building and operating LLM systems in production, Experience deploying agentic systems with real users, Strong full-stack development experience, Hands-on experience with LLM APIs, RAG, prompt engineering, Experience with at least one agentic framework or custom orchestration, Ability to design, ship, and maintain systems end-to-end, Experience with cloud infrastructure and production deployments, Strong written English 📃 Skills: TypeScript, React, Node.js, Python, PostgreSQL, AWS, Anthropic, OpenAI, LangGraph, CrewAI, RAG, LLM, APIs, SQL, VectorDB 🏢 Description: Who we are AgentX is a platform for building and running production AI agents — and a team that ships real systems on top of it for clients who need more than a demo. The platform is the infrastructure: orchestration, memory, tools, evals, deployment — the layer that makes agentic systems actually work in production, not just in a notebook. On top of it, we build end-to-end solutions for our clients. One of the systems running on AgentX today is KsięgoBoty — a multi-agent product used daily by hundreds of Polish accounting firms. Paying customers, production load, real consequences when something breaks. We've also done to ourselves what we build for others: restructured how we work around AI tools, agent-first architectures, and a delivery model that doesn't need a Jira layer between thinking and shipping. This isn't theory — it's how we operate every day. Who we're looking for A senior engineer who owns outcomes, not tasks. This isn't a role for someone who's shipped "an LLM demo at a hackathon." We need someone who has already put agentic systems into production — with real users, real edge cases, real 2am Slack messages when something goes sideways. If you need a PM to translate the problem, a Jira board with three rounds of grooming, and acceptance criteria to tell you what "done" means — this isn't for you, and that's fine. If instead you read a Slack message like "accountants are losing 2 hours a day reconciling this" and your brain immediately jumps to "okay, what does the user actually need, what's the simplest thing that works, and how do we ship it" — keep reading. You'll own problems end-to-end. Frontend, backend, the agent layer, the deploy, the follow-up when a customer hits something weird. You decide what to build, you build it, you ship it, you watch what happens. And you get that this actually matters. On the other end of every feature there's an accountant closing books at 9pm, a firm owner trying to keep their business running. It's not just code. What "AI-native" actually means here Not "I've used ChatGPT." We mean: Claude Code / Cursor / Codex is your IDE , not a plugin you switch on when you feel like it. You know when "accept all" is safe and when it absolutely isn't. You have strong opinions on agent orchestration — when to reach for LangGraph/CrewAI/Agno vs. when to write 50 lines of plain Python that work better. You understand production reality of LLM systems — guardrails, evals, observability, retry logic, cost control, what to do when a model is non-deterministic in a way that breaks your contract with the user. You can tell when a model is the wrong tool and reach for code instead. For you, AI is a tool — not the point. What you'll actually own Agentic systems in production — multi-step workflows, RAG pipelines, agent orchestration. From architecture decision to deployment to the 3am on-call when something drifts. The AgentX platform itself — the primitives, the orchestration layer, the evals, the deployment story. You're building the thing that makes every client engagement faster and more reliable than the last. Full-stack client solutions on top of AgentX — TypeScript/React on the frontend, Python on the backend, integrated with LLM providers (Anthropic, OpenAI, others as they come). Infrastructure that holds up — Postgres, AWS, vector stores, ingestion pipelines, the unsexy layer that makes everything else possible. Quality standards for AI systems — you help us define what "good" looks like. Evals, guardrails, failure modes. Because "mostly right but wrong in scary ways" is not a feature. Our stack TypeScript, React, Node.js, Python, PostgreSQL, AWS, Anthropic + OpenAI APIs, agentic frameworks. You don't need every box ticked — you need to be the kind of specialist who picks up unfamiliar pieces quickly and confidently. What we expect (must-haves) 5+ years shipping production software , at least 1-2 of them with real LLM systems in production — not side projects, not demos Strong full-stack background — you're comfortable owning from frontend to infra, even if your center of gravity is one side AI-native coding workflow — Claude Code, Cursor, Codex, whatever — as your daily driver Hands-on with LLM APIs, RAG, prompt engineering, and at least one agentic framework (or you've built your own orchestration and have opinions on why) Strong written English — you'll communicate with clients, partners, and async teammates Ability to run a project from discovery to delivery with minimal supervision — we'll align on outcomes, you'll figure out how Nice-to-have Experience building B2B SaaS for non-technical users (SMBs, professional services) Voice agents, real-time systems (LiveKit or similar) Accounting / fintech / regulated domain exposure How we work Fast pace, but Monday to Friday. Weekends are yours. We don't do crunch, we don't do fake urgency, we don't do meetings that could've been a message. We'd rather ship steadily for years than sprint for six months and lose you. Direct line to the founder. Direct line to clients. No process layer between you and the work. Small team, real decisions, real ownership. The honest pitch Real ownership of real product areas — not a seat on a feature factory Frontier work — you're building both the platform that makes production agents work and the client systems running on top of it Compensation that reflects seniority — 14 000 – 25 000 PLN netto + VAT (B2B), with room above for someone exceptional Fully paid AI stack — Claude Max, Cursor, whatever you need to work at full speed Remote-first , flexible hours, Poland-based No filler meetings, no Jira bloat — we measure shipped systems in production, not hours logged Push back on the founder when he's wrong. He will be, regularly. How the process works 1. You send us stuff recruitment@agentx.so Your CV — yes, we read them One thing you built end-to-end you're proud of — and what you'd change about it today One AI product (yours or someone else's) you think is genuinely good, and why Your take: a client says our agent is "mostly right but wrong in ways that scare them." What do you do first? 2. We reply within 2-3 days — either "let's talk" or "not this time, here's why." No black hole. 3. We meet — 30-45 min call with the founder. We talk about your work, you ask us hard questions. If the chemistry isn't there, no hard feelings. 4. Problem-solving session (top 2-3 candidates) — we give you a real problem we're working on. You come back with how you'd approach it: your thinking, your trade-offs, your questions. We're not watching over your shoulder. We want to see how you think. 5. Decision within 2-3 days. If yes — you start when you're ready. Tomorrow, next week, after notice period. Your call.

🏢 Summary: The role focuses on designing and building scalable, cloud-native data platforms to enable advanced analytics and reporting across a large internal data ecosystem. It involves developing distributed data pipelines, lakehouse architectures, and optimised data warehousing solutions with strong emphasis on performance, governance, and reliability. The position requires deep technical expertise in big data technologies and cloud-native infrastructure, including on-call responsibility for platform stability. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Commercial experience with Apache Spark for distributed data processing, Hands-on experience with Delta Lake and/or Apache Iceberg in production, Experience with dbt for SQL transformations, Experience with Databricks and Snowflake, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Understanding of performance tuning and cost optimisation in large-scale data systems, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. Over 75% of our business has transitioned to our cloud platform, and we are making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you build will have real consequence. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As an Advanced Data Platform Engineer, you'll design and implement scalable, cloud-native data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services to support diverse analytical use cases at enterprise scale. The role emphasises technical depth — performance optimisation, governance best practices, and the kind of engineering rigour that keeps vast datasets accessible, secure, and compliant. You'll work closely with internal teams to deliver curated datasets and self-service analytics capabilities, and you'll participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems design Design and implement complex data pipelines and distributed systems using Spark and Python, applying clean code principles, modular design, CI/CD, automated testing, and thorough code reviews. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Apache Iceberg, ensuring reliability, performance, and long-term maintainability at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Deliver curated datasets and self-service analytics capabilities that empower internal stakeholders to explore data independently. Data warehousing optimisation Optimise Databricks and Snowflake environments for performance and scalability. Drive cost optimisation and performance tuning across Spark jobs and cloud-native infrastructure. Observability and governance Implement observability and governance frameworks including data lineage tracking and compliance controls, ensuring data remains secure and auditable. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in Python and SQL — the foundation for everything you'll build here. Apache Spark Solid experience with Spark for distributed data processing at scale, including performance tuning and optimisation. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the tradeoffs and have used these in production environments. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and SQL transformation pipelines. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Scalability and cost optimisation Understanding of performance tuning, scalability strategies, and cost optimisation for large-scale data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 160,000 – 240,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Frontend Engineer role focused on building and owning the UI layer of production-ready AI products for B2B clients using TypeScript and React. The position involves developing performant, maintainable interfaces, integrating REST APIs, and handling real-time data flows in close collaboration with backend engineers. This is a hands-on role working on client-facing AI systems where usability and reliability are critical. 🗂️ Requirements: 3–5 years of experience building production frontend applications, Strong experience with TypeScript and React, Experience integrating REST APIs, Experience handling asynchronous UI states, Ability to manage authentication, loading, and streaming states, Experience with SSE or WebSockets, Ability to read and debug Python and FastAPI code 📃 Skills: TypeScript, React, Vite, REST, SSE, WebSockets, Python, FastAPI, Tailwind, shadcn 🏢 Description: About Agentica Agentica is an AI automation startup that designs and deploys custom AI products and agents for B2B clients worldwide. The company builds production-ready AI systems that automate and replace manual business processes across helpdesks, internal tools, e-commerce, production, and other high-friction areas. Its team delivers practical agentic AI solutions for clients ranging from cybersecurity software distributors to global Web3 companies. The Role You’ll own the frontend layer of AI products and client projects, working mainly with TypeScript and React. This is hands-on work on production systems where usability, performance, and reliability matter. You’ll work closely with the tech team and be responsible for shipping clean, maintainable UI code ready for client use. What You’ll Do Build and maintain frontend applications using TypeScript, React, and Vite. Collaborate with backend engineers to integrate REST APIs and manage async data flows. Prototype new interfaces with clients in early stages. Implement clean, extensible component architectures. Handle auth states, loading states, and streaming data (SSE / WebSockets). Read and debug Python / FastAPI backends when needed. Guide coding agents while ensuring code quality. What We’re Looking For Clear communication and strong ownership. AI-first mindset and ability to learn quickly. 3–5 years building production frontend applications. Strong TypeScript and React experience. Experience integrating APIs and handling async UI states. Comfortable reading Python / FastAPI code. Nice to Have Tailwind CSS or component libraries (e.g., shadcn/ui). B2B SaaS or enterprise product experience. What We Offer Attractive salary PLN 12,000–20,000 depending on experience. High-ownership projects with real technical depth and steep learning curves. Early-stage leverage: join while the company is scaling fast and shape how it grows. Fully remote or hybrid from our office in central Warsaw. Flexible working hours built around output, not presence. A senior, technically sharp team with hands-on AI and software delivery experience. Apply now and build leading AI products. Join a team that cares about quality, ownership, and real client impact.

🏢 Summary: Mid-level React/TypeScript Engineer role focused on building and owning production-grade frontend applications (dashboards, operator panels, customer apps) on top of AI agent systems. The position involves close collaboration with backend services and active use of AI coding tools while maintaining strong engineering judgment and code quality. You will take full ownership of features from design to deployment in a production environment with real users. 🗂️ Requirements: 3–5 years commercial experience in frontend development, Strong proficiency in TypeScript, Deep understanding of React and rendering lifecycle, Experience building scalable frontend architectures, Experience integrating with REST APIs and authentication systems, Ability to work with backend technologies (Node.js or Python), Experience with state management and data synchronization, Proficiency with Next.js, Experience working with MongoDB, Experience deploying or working with AWS, Ability to use AI coding tools critically and effectively 📃 Skills: TypeScript, React, Next.js, Tailwind, Node.js, Python, MongoDB, AWS, REST, Claude, Cursor, MCP 🏢 Description: Who we are AgentX is a platform for building and running production AI agents - and a team that ships real systems on top of it for clients who need more than a demo. The platform is the infrastructure: orchestration, memory, tools, evals, deployment - the layer that makes agentic systems actually work in production. On top of it, we build end-to-end solutions for our clients. One of the systems running on AgentX today is KsięgoBoty - a multi-agent product used daily by hundreds of Polish accounting firms. Paying customers, production load, real consequences when something breaks. We're small, technical, AI-heavy, and we ship. Who we're looking for A solid React engineer who actually understands what's happening under the hood, and uses AI tools daily without outsourcing their brain to them. You'll join the team that owns the user-facing layer of our products: the dashboards, the operator panels, the customer-facing apps that sit on top of the agents. We need someone we can trust to take a feature, build it well, and ship it without it coming back broken three days later. This isn't a flashy role and we're not looking for a flashy person. We need craftsmanship. If you read a ticket and your first instinct is "what's the data model, what's the component structure, where does state actually live" - keep reading. If your first instinct is "I'll just vibe-code it with Cursor and hope the PR passes" - this isn't for you, and that's fine. What we mean by "good React engineer" You write TypeScript well: types help you, they don't slow you down You understand React deeply enough to debug a re-render problem without guessing You can structure a non-trivial frontend so it doesn't turn into a tangle in six months You've worked with a real backend: REST, auth, data sync, edge cases — and you can hold both ends of a feature in your head You read other people's code carefully and review like an adult: kindly, but honestly You are comfortable using AI tools daily, but you do not outsource your judgment to them You know how to check AI-generated code instead of trusting it because it “looks right” ~3–5 years of commercial experience is roughly where we expect this person to sit. Less is fine if you're sharp; more is fine if you actually want a Mid role. How we work with AI We use AI heavily. Claude Code, Codex, Cursor, MCP, agent workflows: they're a normal part of how we work, the same way Git or Docker is. You'll be expected to use them the same way: not as a gimmick, not as a shortcut around understanding the codebase, but as leverage. That means: break work into clear chunks, guide the tools through implementation, review their output critically, fix what's wrong, and own the final result. You should be faster with these tools than without them - and you should know exactly where they're about to lie to you. AI doesn't turn a bad engineer into a good one. It just makes them ship faster, which is worse. So: We do not want people who only know how to prompt. We also do not want people who proudly refuse to use AI and treat it like autocomplete with better marketing. The right person sits in the middle: strong fundamentals, strong taste, strong ownership - multiplied by modern AI tooling. What you'll actually own Frontend, day-to-day. React, TypeScript, Tailwind, Next.js. Real product surfaces - operator dashboards, customer panels, internal tools that real people use to do real work. Fullstack when needed. You won't live exclusively in the frontend. Node/Python on the backend when a feature needs it - you don't have to be an expert, but you have to be willing. Quality. The thing you ship works, doesn't break the next thing, and doesn't make the codebase worse. We notice this. Working with the team. Code reviews, architecture decisions - we figure out the harder calls together. You're not coding in a vacuum. The stack TypeScript / React / Next.js · Tailwind · Node.js · Python (some) · MongoDB · AWS · Claude / Cursor / MCP for tooling. We don't use Go. Nice-to-have (not required) You've built a side project that you actually shipped, not just started You've worked with LLM APIs in production (not "I made a chatbot in a tutorial") You care about UX - not as a designer, but as someone who notices when something feels wrong What we offer 13 000 – 18 000 PLN netto + VAT, B2B Remote-friendly, Poland-based A small team that ships and doesn't waste your time Direct work with the founders - no Jira theater, no three-round groomings, no PM filtering your ideas Modern AI tooling fully paid for (Claude Max, Cursor, Codex, whatever helps you work better) Real ownership of the frontend layer of a product people use every day How the process works 1. You send us stuff recruitment@agentx.so Your CV — yes, we read them One thing you built end-to-end you're proud of — and what you'd change about it today One AI product (yours or someone else's) you think is genuinely good, and why Your take: a client says our agent is "mostly right but wrong in ways that scare them." What do you do first? 2. We reply within 2-3 days — either "let's talk" or "not this time, here's why." No black hole. 3. We meet — 30-45 min call with the founder. We talk about your work, you ask us hard questions. If the chemistry isn't there, no hard feelings. 4. Problem-solving session (top 2-3 candidates) — we give you a real problem we're working on. You come back with how you'd approach it: your thinking, your trade-offs, your questions. We're not watching over your shoulder. We want to see how you think. 5. Decision within 2-3 days. If yes — you start when you're ready. Tomorrow, next week, after notice period. Your call.

🏢 Summary: Frontend Engineer role focused on building AI-powered web applications and GenAI interfaces using React and TypeScript for enterprise clients. The position involves designing responsive conversational UIs, integrating with APIs and LLM services, and solving modern AI interaction and UX challenges. The role offers flexible work arrangements, professional development, and exposure to cutting-edge AI product engineering. 🗂️ Requirements: 3+ years commercial frontend development experience, React, TypeScript, Modern frontend architecture, State management, Component design, Performance optimization, Responsive design, REST APIs, WebSockets, Streaming endpoints, UX design understanding, AI-powered interfaces familiarity or interest, AI-assisted development tools, English B2+ 📃 Skills: React, TypeScript, REST, WebSockets, Cursor, Copilot, Next.js, D3.js, Recharts, Visx, WCAG, Playwright, Cypress, Node.js, Python, FastAPI 🏢 Description: WHO WE ARE Accenture is a leading global professional services company that helps the world’s leading businesses, governments, and other organizations build their digital core, optimize their operations, accelerate revenue growth, and enhance citizen services. At the AI&Data, we work locally and globally with over 200 Poland-based specialists. Our expertise spans data architecture and sectoral specialization. We collaborate with tech partners like Microsoft, AWS, Google, Oracle, and Snowflake to implement cutting-edge solutions. We provide comprehensive support from strategy definition to solution implementation and development, covering all aspects of Data & Analytics. THE WORK As a Frontend Engineer – AI Solutions, you will design and build the user-facing layer of GenAI and agentic AI solutions for leading global enterprises. You’re the person who makes powerful AI systems usable – turning complex agent interactions, streaming LLM outputs, and enterprise data into intuitive, polished product experiences. We’re looking for someone who is React-strong, thinks in terms of user experience, and is excited about solving the unique UI/UX challenges that come with building AI-powered products. Understanding of frontend security best practices – including authentication and authorization flows, secure API integrations, and protection against common web vulnerabilities , is crucial on this position. You will: Build modern, responsive frontends for GenAI products using React and TypeScript – conversational interfaces, agent dashboards, data exploration tools, and interactive analytics views Design and implement AI-specific interaction patterns: streaming chat, real-time agent status, citation rendering, confidence indicators, and graceful handling of AI uncertainty Own the UX quality of AI products – making deliberate decisions about information architecture, component design, accessibility, and how users interact with AI outputs Integrate frontends with backend APIs, LLM services, and streaming endpoints – working closely with GenAI engineers to deliver seamless end-to-end experiences Collaborate with engineers, designers, and consultants on cross-functional teams, shaping how enterprise users experience AI Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office – depending on specific project circumstances. With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs. WHAT’S IN IT FOR YOU? Build the interface layer of cutting-edge AI: you’ll shape how users actually experience GenAI – the part that makes the difference between a demo and a product. Solve UI/UX problems that barely exist yet: streaming agent interactions, multi-agent status views, conversational analytics – these design patterns are being invented right now, and you’ll be the one inventing them. Grow at the intersection of frontend engineering and AI: work alongside experienced AI & Data practitioners, gaining unique product engineering expertise that very few frontend developers have today. Qualification HERE’S WHAT YOU’LL NEED Min. 3 years of commercial experience in frontend development Strong proficiency in React and TypeScript Solid understanding of modern frontend architecture – state management, component design, performance optimization, and responsive design Experience integrating frontends with REST APIs, WebSockets, or streaming endpoints Strong UX sensibility – ability to make deliberate design and interaction decisions, not just implement mockups Familiarity with AI-powered product interfaces (chatbots, conversational UIs, dashboards with AI-generated content) or a strong interest in this space Proficiency with AI-assisted development tools (e.g., Cursor, Copilot, or similar) – we expect these to be a core part of your daily workflow, not an occasional add-on Good command of English (min. B2+) BONUS POINTS IF YOU HAVE Experience building real-time or streaming UIs (e.g., Server-Sent Events, WebSocket-based interfaces) Hands-on experience with UI component libraries and design systems (e.g., Shadcn, Radix, Material UI) Familiarity with Next.js or similar full-stack React frameworks Basic understanding of LLMs, prompt engineering, or how GenAI APIs work Experience with data visualization libraries (e.g., D3.js, Recharts, Visx) Knowledge of accessibility standards (WCAG) and inclusive design practices Experience with frontend testing (e.g., Playwright, Cypress, React Testing Library) Basic backend or API development experience (Node.js, Python, FastAPI) Research indicates that some candidates, especially the most diverse ones, may hesitate to apply for positions if they don’t meet all requirements. If you believe you possess the necessary skills, even if not meeting every requirement, we wholeheartedly encourage you to submit your application. WHAT WE OFFER? A permanent employment contract Individual support of a People Lead and a clearly defined path of professional development, including the possibility of a session with a Coach A comprehensive training package, including: soft skills, technical and language training, access to e-learning platforms, Gallup test, GenAI training, possibility of co-financing courses and certifications Employee Assistance Program offering legal, financial and psychological consultations Employee Share Purchase Plan – employees who own company shares are automatically eligible for quarterly dividends Paid employee referral program Private medical care and life insurance Access to the Worksmile benefits platform (including the Multisport card) Interview Note: We value practical skills. During the technical interview, we’ll give you a real problem to solve and debug together – using your preferred development setup, including any AI-assisted tools you work with day to day. WHAT WE BELIEVE: Accenture does not discriminate employment candidates on the basis of race, religion, color, sex, age, disability, national origin, political beliefs, trade union membership, ethnicity, denomination, sexual orientation or any other basis impermissible under Polish law. All our leaders are committed to building a better, stronger and more durable company for future generations to create positive, long-lasting change. Inclusion and diversity are fundamental to our culture and core values. Our rich diversity makes us more innovative and creative, which helps us better serve our clients and our communities. Our position as partner to many of the world’s leading businesses, organizations and governments affords us both an extraordinary opportunity and a tremendous responsibility to make a difference. Sustainability is one of our greatest responsibilities, which we embed it into everything we do and for everyone we work with. Clicking apply I hereby express my consent to process my personal data included in my job offer by Accenture Sp. z o.o. or any other entity of the Accenture group for recruitment purposes, and that it is a data controller within the meaning of GDPR. More information about Accenture (and if necessary also its representative) can be found here: https://www.accenture.com/pl-pl/privacy-policy #LI-EU

🏢 Summary: Hands-on Lead Cloud Platform Engineer role focused on owning, securing, automating, and optimizing an Azure-based SaaS and AI infrastructure, including Azure Databricks and DevSecOps practices. The position covers end-to-end cloud governance, Kubernetes operations, CI/CD, security, and cost optimization in a large-scale data environment. This is a senior technical role with potential growth into technical or people leadership. 🗂️ Requirements: 7+ years in DevOps/Cloud/Platform/Infrastructure engineering, 4+ years hands-on Azure production experience, Strong Azure governance, RBAC, policies, networking, storage, monitoring, security, Experience with Entra ID and Microsoft 365 administration, Production Kubernetes experience (AKS preferred), Experience managing Azure Databricks infrastructure, CI/CD experience with Azure DevOps and/or GitHub Actions, Scripting skills (PowerShell, Azure CLI, Bash, or Python), Knowledge of cloud security principles (least privilege, secrets management, encryption, auditability), Ability to work independently and drive platform improvements 📃 Skills: Azure, Databricks, DevSecOps, AKS, Kubernetes, EntraID, Microsoft365, AzureDevOps, GitHubActions, Terraform, Bicep, ARM, PowerShell, AzureCLI, Bash, Python, ADLS, Blob, AzureSQL, KeyVault, VNets, DNS, NSG, RBAC, CI/CD, FinOps, Defender, SOC2 🏢 Description: An AI-powered consumer intelligence platform is hiring a Lead Cloud Platform Engineer (Azure, Databricks & DevSecOps). Our platform processes 50+ billion data points monthly to deliver actionable insights for leading global brands, such as Coca-Cola, Unilever, and Bayer. We run on Azure, Databricks, and GenAI workflows, and we're scaling our platform for faster delivery, stronger security, and tighter cost discipline. The Role We're hiring a hands-on cloud platform leader to own, secure, automate, and optimize our Azure-based SaaS and AI infrastructure end to end. You'll own Azure administration, Entra ID and Microsoft 365, networking, storage, Kubernetes, security, CI/CD, and FinOps, plus the cloud platform layer around Azure Databricks (networking, identity, secure access, compute governance, monitoring, and cost control). This is a hands-on role first, with a clear path to technical or people leadership as the company grows. What You'll Do • Own Azure subscriptions, governance, networking (VNets, private endpoints, DNS, NSGs), storage (ADLS Gen2, Blob), Azure SQL, Key Vault, and monitoring across all environments. • Administer Entra ID and Microsoft 365 - identities, MFA, Conditional Access, least-privilege access, and joiner/mover/leaver processes. • Manage Azure Databricks infrastructure and security: secure connectivity, networking, identity integration, compute policies, audit logging, and cost controls. • Build and improve CI/CD (Azure DevOps, GitHub Actions) and introduce Infrastructure as Code (Terraform, Bicep, or ARM) to replace manual portal changes. • Operate and secure Kubernetes/AKS environments and supporting application infrastructure. • Strengthen security and DevSecOps posture; support SOC 2 evidence, security questionnaires, and enterprise reviews. • Build monitoring, dashboards, runbooks, and incident response across the platform. • Drive Azure and Databricks cost optimization through tagging, budgets, alerts, and compute tuning. What You'll Bring: Required Qualifications • 7+ years in DevOps, Cloud, Platform, Infrastructure, or Systems Engineering, including 4+ years hands-on with Azure in production. • Strong Azure depth: subscriptions, RBAC, policies, networking, storage, monitoring, and security. • Solid experience with Entra ID and Microsoft 365 administration. • Production Kubernetes experience (AKS preferred). • Experience managing or supporting Azure Databricks infrastructure (workspace admin, compute, networking, secure storage access, identity, audit logging). • CI/CD experience with Azure DevOps and/or GitHub Actions, plus scripting (PowerShell, Azure CLI, Bash, or Python). • Strong grasp of cloud security: least privilege, secrets management, encryption, and auditability. • Proven ability to work independently, create structure, and drive improvements with minimal supervision. Nice to Have: Preferred Qualifications Experience in AI, data, analytics, or SaaS environments; Infrastructure as Code (Terraform, Bicep); SOC 2 / ISO 27001 / GDPR; Microsoft Defender for Cloud and DevSecOps tooling; FinOps and Databricks cost optimization; and working with distributed or offshore teams. What This Role Is Not This role is not a pure CI/CD role, a helpdesk-only M365 admin role, a Databricks notebook developer, a data engineering role, or a people-management role. The Opportunity • Long-term B2B contract opportunity • High Impact: We’re backed by world-class investors and work with the most iconic global consumer brands. • You’ll have ownership, with a clear path to technical or people leadership as the company grows..

🏢 Summary: Senior full-stack product engineering role focused on applying AI agents and frontier models to automate worker sourcing, vetting, matching, and fulfillment across a large-scale staffing marketplace. You will build and scale core systems including real-time matching, autonomous vetting pipelines, and distributed APIs, partnering closely with the CTO on architecture and roadmap. The role spans frontend, backend, and AI integrations, shipping production-ready automation in a fast-moving environment. 🗂️ Requirements: 5+ years experience in frontend and backend development, Proficiency in TypeScript, Proficiency in React or React Native, Proficiency in Node.js or Python, Strong experience with APIs, Experience with distributed systems, Experience with PostgreSQL, Experience with Kafka or RabbitMQ, Hands-on experience integrating LLMs or AI agents into production products, Proven experience shipping scalable applications in early-stage environments 📃 Skills: TypeScript, React, ReactNative, Node.js, Python, APIs, DistributedSystems, PostgreSQL, Kafka, RabbitMQ, LLMs, AI, Agents 🏢 Description: You'll build Traba's product on top of AI agents—taking frontier models and existing agents and putting them to work across the staffing marketplace to automate the pipeline that sources, vets, matches, and places workers on millions of shifts. This is a product-engineering role focused on applying AI in real product environments, partnering with the CTO on architecture and roadmap, and building the platform the company runs on. About You: An applier, not a researcher. You take frontier models and existing agents and wire them into real product across the stack—shipping reliable automation rather than owning the orchestration internals. You focus on the highest-priority problems, whether AI-driven or not. Voracious learner, comfortable moving between API design, UX, and deployment infrastructure. Proven full-stack builder with a track record of shipping scalable, performant applications from frontend interfaces to backend distributed systems. You Will: Apply existing agents and frontier models across the stack—worker app, business app, ops platform, marketplace—to automate vetting, matching, and fulfillment. Lead frontend and backend development and mentor other engineers. Architect and build core systems including real-time matching, autonomous vetting pipelines, distributed systems, and APIs. Own product surfaces end to end, partnering closely with product and design. You Have: 5+ years across frontend and backend: TypeScript, React/React Native, and Node.js or Python. Strong experience with APIs, distributed systems, PostgreSQL, and messaging (Kafka or RabbitMQ). Hands-on experience integrating LLMs or agents into real products, including prompting, tool wiring, and evaluations. Track record of shipping scalable products in fast, ambiguous, early-stage environments. Benefits: Start-up equity Competitive salary ($200,000–$240,000) 100% paid health, dental, and vision coverage Dinner provided via DoorDash, free DashPass, and stocked kitchen for NY employees Commuter benefit Gympass benefit Additional benefits: One Medical membership, HSA via Optum, Talkspace, HealthAdvocate, Teledoc Health Equal Opportunity Employer: All applicants are evaluated without discrimination based on legally protected characteristics.

🏢 Summary: Senior/Lead .NET 8+ Backend Engineer role focused on building a secure, scalable AI-powered platform on Azure with a controlled RAG layer. The position involves designing REST APIs, implementing data access with EF Core and SQL Server, and ensuring strong security, auditability, and cloud integration. You will work within an Agile team, contributing to architecture, infrastructure automation, and AI-assisted development practices. 🗂️ Requirements: Senior/Lead experience with .NET 8+ and C#, Hands-on experience with Azure (Entra ID, Azure SQL, App Service or Container Apps, Blob Storage, Key Vault), Experience with REST API development and OpenAPI (documentation, versioning, contracts), Strong knowledge of SQL Server and EF Core (migrations, query optimization), Experience with data warehouses, Experience with Docker and Terraform, Knowledge of application security (data isolation, encryption, auditability), Experience integrating external APIs, Proficiency with AI development tools (e.g., GitHub Copilot), Very good English (spoken and written) 📃 Skills: .NET, C#, Azure, EntraID, AzureSQL, AppService, ContainerApps, BlobStorage, KeyVault, SQLServer, EFCore, REST, OpenAPI, Docker, Terraform, OpenAI, GitHubCopilot, RAG, xUnit, Angular, MediatR, Polly 🏢 Description: The client is building a component — an AI-powered platform optimizing the full field-work cycle of consultants, turning dispersed data into actionable business recommendations. The solution is built on a modular Azure architecture with a controlled RAG layer, ensuring full auditability, data sovereignty, and seamless integration with the client's existing technology ecosystem. Requirements: Very strong .NET experience (.NET 8+ and C# at senior/lead level) Experience with Azure cloud environments: Entra ID (SSO, MFA, RBAC), Azure SQL, App Service or Container Apps, Blob Storage, Key Vault Docker, Terraform Integration experience: REST API and OpenAPI (documentation, contracts, versioning) Strong knowledge of SQL Server and EF Core (migrations, query optimization) Experience with data warehouses Application security: data isolation, encryption, auditability AI Tooling: Proficiency with tools like GitHub Copilot to maximize productivity and code quality Strong communication skills and ability to clearly articulate technical ideas Very good English (spoken and written) Nice to have: Clean Architecture / CQRS, MediatR Polly (retry, circuit breaker) and external API integration Basic understanding of RAG and LLM APIs (session context, conversation history) xUnit, integration testing Angular — sufficient proficiency to design API contracts for frontend needs Main responsibilities: Designing and delivering secure, scalable, and maintainable .NET 8+ / C# backend solutions within a cross-functional Agile team Building and maintaining REST APIs with full OpenAPI documentation, versioning, and contract-first design to support frontend and third-party integrations Working with Azure cloud services including Entra ID (SSO, MFA, RBAC), Azure SQL, App Service or Container Apps, Blob Storage, and Key Vault Implementing and maintaining data access layers using EF Core and SQL Server, including migrations, query optimization, and data warehouse integrations Ensuring application security best practices: data isolation, encryption, and auditability Contributing to infrastructure automation using Docker and Terraform Providing technical guidance, participating in solution design, and supporting architectural decisions across the team Troubleshooting and maintaining existing codebases, including components developed by other engineers Leveraging AI development tools (e.g. GitHub Copilot) to enhance productivity and code quality Documenting technical decisions, architecture, and progress in accordance with project and compliance requirements Preparing reliable estimates and taking full ownership of assigned deliverables Staying current with modern engineering practices and emerging technologies relevant to the stack Tech stack: .NET v8+ and C# EF Core Azure: Entra ID (SSO, MFA, RBAC), Azure SQL, App Service or Container Apps, Blob Storage, Key Vault RestAPI and OpenAI SQL Server AI tooling