AI Full-Stack Developer

🏢 Summary: Senior-level role focused on designing and delivering scalable AI/ML solutions, including LLMs, RAG, and agent-based systems, from architecture to production deployment. The position involves leading technical decisions, writing high-quality Python code, and building cloud-based microservices solutions. The role also requires translating business needs into robust, production-ready AI systems. 🗂️ Requirements: Several years of software development experience (senior-level), Strong Python proficiency, Solid understanding of ML/AI ecosystem (LLMs, NLP, deep learning), Hands-on experience with RAG, prompt engineering, agent-based systems, Experience with microservices architecture, Experience with databases, Experience with Kubernetes, Experience with CI/CD pipelines, Experience with Azure cloud, English proficiency 📃 Skills: Python, LLMs, RAG, NLP, DeepLearning, PromptEngineering, Microservices, Databases, Kubernetes, CICD, Azure, GCP, Java 🏢 Description: Responsibilities: Design and develop scalable AI/ML solutions (LLMs, RAG, agentic systems) Write high-quality, testable Python code Lead technical architecture and make key design decisions for critical projects Own end-to-end delivery of solutions, from design to production deployment Collaborate with business stakeholders and translate requirements into technical solutions Requirements: Several years of experience as a software developer (senior-level preferred) Very strong Python skills and solid understanding of the ML/AI ecosystem (LLMs, NLP, deep learning) Hands-on experience with RAG, prompt engineering, and agent-based systems Experience with microservices architecture, databases, Kubernetes, and CI/CD pipelines Experience with Azure cloud (GCP as a plus) Basic familiarity with Java is a plus Strong English communication skills

🏢 Summary: Senior AI Engineer role focused on building and deploying production-grade AI solutions using Python, FastAPI, Azure, Generative AI, RAG, and agentic frameworks in a hybrid work model. The position includes backend architecture, AI pipeline development, MLOps ownership, and mentoring responsibilities. 🗂️ Requirements: 6–10 years of software engineering experience, Strong AI/ML engineering background, Expertise in Python, Expertise in FastAPI, Experience with LLMs, Experience with RAG pipelines, Experience with vector databases, Hands-on experience with agentic AI frameworks, Production experience with Azure cloud services, Knowledge of MLOps, Experience with Docker, Experience with Kubernetes, Experience with CI/CD 📃 Skills: Python, FastAPI, Azure, LLMs, RAG, Pinecone, Milvus, LangChain, LangGraph, AutoGen, CrewAI, Docker, Kubernetes, CI/CD, MLOps, AKS 🏢 Description: Location: Wroclaw, Poland (Hybrid: 3 days/week in-office) Experience: 6–10 years About the Role We are looking for a Senior AI Engineer to design, develop, and deploy production-grade AI solutions using Python, FastAPI, and Azure, with a strong focus on Generative AI, LLMs, RAG, and agentic frameworks. Key Responsibilities Architect and implement scalable backend services with Python and FastAPI . Build and optimize RAG pipelines using vector databases (e.g., Pinecone, Milvus, Azure Cognitive Search). Develop autonomous agents using agentic AI frameworks (LangChain, LangGraph, AutoGen). Deploy and manage AI workloads on Azure (Azure ML, AKS, OpenAI Service). Own the full ML lifecycle: experimentation, versioning, CI/CD, and monitoring. Mentor junior engineers and drive technical best practices. Required Skills 6–10 years of software engineering experience, with strong focus on AI/ML. Expert in Python and FastAPI . Deep experience with LLMs , RAG , and vector databases . Hands-on experience with agentic frameworks (LangChain, CrewAI, etc.). Production experience with Azure cloud services. Strong understanding of MLOps, containerization (Docker/Kubernetes), and CI/CD.

🏢 Summary: Senior-level role focused on building AI-driven backend applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). The position involves developing scalable APIs, integrating retrieval pipelines, and deploying services in cloud environments. The role combines advanced AI implementation with solid backend engineering practices. 🗂️ Requirements: 5+ years commercial experience in Python development, Strong backend engineering experience (APIs, services, integrations), Hands-on experience with LLMs, Hands-on experience with RAG implementations, Experience with Azure, AWS, or GCP, Knowledge of software development best practices 📃 Skills: Python, LLMs, RAG, Azure, AWS, GCP, APIs 🏢 Description: Senior Python AI Developer We are looking for an experienced Python Developer to join a team building modern AI-driven applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) , alongside standard backend development work. Key Responsibilities Develop and maintain backend services and APIs in Python Build AI-enabled application features using LLMs and RAG workflows Design and integrate retrieval pipelines for contextual AI responses Work with databases, external APIs, and internal systems Deploy and operate services in Azure or other cloud environments Write clean, testable, and scalable production code Requirements 5+ years of commercial experience in Python development Strong background in backend engineering (APIs, services, integrations) Hands-on experience with LLMs and RAG implementations Cloud experience with Azure , AWS, or GCP Solid understanding of software development best practices Tech Stack Python LLMs, RAG Azure (or other cloud platforms)

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI systems, including agentic workflows and RAG pipelines integrated into enterprise platforms. The position emphasizes backend engineering, API integrations, and orchestration of LLM capabilities in secure, scalable cloud environments rather than ML research. The role also includes mentoring engineers and establishing best practices for reliable, observable AI services. 🗂️ Requirements: 5+ years professional software development experience, Proficiency in Python, Experience building production LLM applications, Hands-on experience with RAG systems, Experience designing and integrating RESTful APIs, Strong understanding of distributed systems fundamentals, Experience with SQL databases and performance optimization, Experience with vector search, Experience integrating external services via APIs, Knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Microservices, DistributedSystems, Concurrency, AsyncIO, VectorSearch, Embeddings, Caching, AzureFunctions, Storage, KeyVault, AppConfiguration, ApplicationInsights, ServiceBus, EventHubs 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI solutions, including agentic workflows and RAG pipelines integrated into enterprise systems. The position emphasizes software engineering excellence, cloud-based AI services, and orchestration of LLM capabilities rather than model research. You will build reliable, secure, and observable AI services integrated with internal platforms and APIs. 🗂️ Requirements: 5+ years of professional software development experience, Strong background in designing and operating production systems, Proficiency in Python or another backend language for AI systems, Experience building and integrating RESTful APIs, Understanding of distributed systems fundamentals, Experience with API integrations and event-driven architectures, Solid SQL and database design knowledge, Experience with vector search, Hands-on experience building end-to-end LLM applications, Experience implementing RAG pipelines, Strong knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and regression testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Embeddings, VectorSearch, AzureFunctions, AzureStorage, KeyVault, AppConfiguration, ApplicationInsights 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Lead AI Software Developer role focused on architecting and scaling AI-powered applications, backend systems, and multi-agent workflows across cloud and enterprise environments. The position involves designing secure integrations, optimizing LLM-based solutions, and leading technical delivery and best practices. It combines hands-on AI development with backend architecture and technical leadership. 🗂️ Requirements: Degree in Computer Science, AI, Data Science or related field, 8+ years of software engineering experience, 5+ years of Python backend development in production, Experience building and scaling Python applications, Hands-on experience with AI Agents, RAG and MCP, Experience with AWS or Azure cloud platforms, Experience with storage systems and databases, Knowledge of containerization and Kubernetes, Experience with API integrations and enterprise system connectivity, Leadership and mentoring experience 📃 Skills: Python, AWS, Azure, Kubernetes, RAG, MCP, APIs, Cloud, Databases, Containerization, AI, LLM 🏢 Description: We are seeking an experienced Lead AI Software Developer to design and scale AI-powered applications and integrations. In this role, you will architect backend systems, lead AI agent development, and ensure secure, scalable integration across cloud platforms and enterprise systems. Key Responsibilities Design and maintain middleware, APIs, and connectors integrating AI agents with enterprise systems Architect scalable backend services and cloud-based solutions (AWS/Azure) Develop and optimize multi-agent workflows and adaptive decision logic Fine-tune prompts and LLM-based solutions for domain-specific use cases Lead code reviews, mentor developers, and define development best practices Drive complex API integrations with internal and external AI platforms (incl. MCP servers) Remove technical roadblocks and ensure timely delivery Collaborate with AI, Data, and Platform teams to optimize automation architectures Maintain technical documentation and promote continuous improvement Requirements Degree in Computer Science, AI, Data Science, or similar field 8+ years of software engineering experience, including 5+ years of Python backend development (production) Strong experience building and scaling Python applications Hands-on experience with AI technologies (AI Agents, RAG, MCP) Experience with cloud platforms (AWS or Azure), storage, databases, and AI services Knowledge of containerization and Kubernetes Experience with API integrations and enterprise system connectivity Strong leadership and mentoring experience Excellent communication skills; fluent in Polish and English (min. B2); German is a plus Willingness to travel internationally (~10%) Nice to have: Experience with LangChain, LangGraph, multi-agent systems, prompt engineering, and LLM fine-tuning. What We Offer Work in a global and innovative technology environment Direct impact on enterprise AI and automation solutions Professional development and access to training programs Hybrid work model with flexible hours (central Wroclaw office) Competitive benefits package, cafeteria system, CSR initiatives, and employee clubs

🏢 Summary: Senior Fullstack Engineer role focused on delivering full-stack solutions within an AI-integrated SDLC where AI is embedded across planning, development, review, testing, and deployment. The position combines backend and frontend engineering with AI orchestration, automation, and cloud-native architecture in a remote-first setup. The engineer will also evolve shared AI toolchains and contribute to architectural and code quality standards. 🗂️ Requirements: Team-level AI-integrated SDLC experience across planning, development, review, testing, deployment, Shared AI toolchain management under version control, Hands-on use of Claude Code, GitHub Copilot, Cursor or equivalent as team tools, Building and maintaining custom AI skills and sub-agents for team use, Experience with parallel AI agent orchestration, Spec-driven development using OpenAPI, ADRs, PRDs as AI context, AI-assisted code review integrated into PR process, Working knowledge of AI orchestration frameworks, Backend development with .NET / C# and ASP.NET Core, Frontend development with TypeScript and React or Angular, Experience with SQL databases and ORM frameworks, Experience with Docker and Kubernetes, Experience with CI/CD pipelines, Experience with cloud platforms (Azure, AWS, or GCP) 📃 Skills: C#, .NET, ASP.NET, SQL, SQLServer, PostgreSQL, EFCore, OAuth, JWT, Python, Java, Node.js, TypeScript, JavaScript, React, Angular, LangChain, LlamaIndex, CrewAI, Docker, Kubernetes, GitHubActions, AzureDevOps, Azure, AWS, GCP, OpenAPI, CQRS, DDD, EventSourcing, Microservices 🏢 Description: We are looking for a Senior Fullstack Engineer who combines deep technical expertise with real, team-level experience working in an AI-integrated software development lifecycle. Individual use of AI coding assistants is not sufficient for this role. We are specifically looking for engineers who have worked in teams where AI was embedded into every phase of delivery — from planning and design through development, review, testing, and deployment. We follow a remote-first setup with no mandatory regular office visits for this position. From time to time, you may be invited to join in-person meetings in one of our offices (Warsaw, Lodz, Wroclaw, Gdansk, or Bialystok), for example for client visits or team reunions. AI-First Requirements Experience working in an AI-enabled engineering team is mandatory — not a personal workflow preference. You have been part of a team where AI was systematically embedded across all delivery phases: planning, development, review, testing, and deployment. You can speak from direct experience about how it worked, what failed, and what you would change. Specific mandatory requirements: Team-level AI-integrated SDLC experience — shared toolchain, shared configurations, shared assets under version control Hands-on with Claude Code, GitHub Copilot, Cursor, or equivalent as a team tool, not only personal usage Built and maintained custom skills and sub-agents used across a team, not just personally Experience with parallel agent orchestration for concurrent workstream execution Disciplined plan → review plan → execute approach with AI involved at every phase Maintained shared prompt libraries, skill repositories, or agent configurations in version control AI-assisted code review integrated into the PR process: CodeRabbit, Copilot review, or similar Experience with spec-driven or document-driven development where structured specifications (OpenAPI, ADRs, PRDs) serve as AI context inputs, not just human references Working knowledge of at least one AI orchestration framework: LangChain, LlamaIndex, Microsoft Agent Framework, CrewAI, or equivalent Automation-first mindset: proactively identify repetitive or inefficient parts of current work and automate them using AI and other available tools. Cost-aware AI usage: understanding how AI credits are consumed across different tools, models, and workflows, and ability to choose the most appropriate model or approach for each task. Technical Requirements Backend: .NET / C#, ASP.NET Core, SQL Server / PostgreSQL, EF Core, OAuth 2.0 / JWT. Python, Java, or Node.js is a strong plus. Frontend: TypeScript, JavaScript, React(preferable) and/or Angular, state management, async patterns, frontend testing. Architecture: Full spectrum from monolith to microservices — DDD, CQRS, Event Sourcing, event-driven design, message brokers. Infrastructure: Docker, Kubernetes, CI/CD (GitHub Actions / Azure DevOps), Azure / AWS / GCP, structured observability. Responsibilities Deliver full-stack features to a high standard of quality, performance, and reliability Contribute to architectural decisions and system design trade-offs Evolve and maintain the team's shared AI toolchain across all SDLC phases Conduct code reviews including AI-assisted tooling; uphold and enforce engineering best practices Proactively surface risks, bottlenecks, and security concerns Communicate and collaborate directly with clients in English Mentor engineers on both technical fundamentals and AI-augmented workflow practices Professional Qualities Ownership mindset · Strong written and verbal English · Comfortable in client-facing roles · Raises the AI workflow maturity of those around them

🏢 Summary: Remote Senior FullStack Developer role focused on building and scaling end-to-end AI applications, agentic workflows, and modern front-end interfaces. The position involves designing AI-driven solutions, optimizing system architecture, and integrating LLM-based systems into production environments. You will work on data-heavy applications and enterprise automation within a fully remote project in Poland. 🗂️ Requirements: 5+ years of experience with Python for data-heavy or AI-integrated applications, Strong experience with Django, Flask or FastAPI, Strong mastery of Vanilla JavaScript, Hands-on experience with AngularJS and knowledge of migration to modern Angular, Experience building agentic AI systems and autonomous LLM-based workflows, Practical knowledge of LangChain, LlamaIndex and RAG, Experience with AI agent orchestration frameworks, Commercial experience with GCP or AWS, Proven experience with Google AppScript for enterprise automation, Strong understanding of RESTful APIs, Experience with asynchronous programming, Experience with end-to-end agentic workflows, Hands-on experience with GenAI technologies such as Gemini, Copilot or Claude 📃 Skills: Python, Django, Flask, FastAPI, JavaScript, AngularJS, Angular, LangChain, LlamaIndex, RAG, LLM, GCP, AWS, AppScript, REST, GenAI, Gemini, Copilot, Claude 🏢 Description: This is a remote position. As a Senior FullStack Developer at Virtusa , you will build and scale end-to-end AI applications, integrate automated workflows, and design intuitive front-end interfaces. You will diagnose architectural bottlenecks, propose AI-driven optimizations, and communicate directly with stakeholders to turn complex requirements into functional code. This is a fully remote project within Poland. Requirements At least 5 years of experience with Python (Django, Flask, or FastAPI), specifically for data-heavy or AI-integrated applications. Strong mastery of Vanilla JavaScript and hands-on experience with Angular JS (and familiarity with the migration path to modern Angular). Hands-on experience building agentic AI systems and autonomous workflows based on LLMs. Strong practical knowledge of: LangChain, LlamaIndex, RAG, AI agent orchestration frameworks. Commercial cloud experience: GCP (preferred) or AWS AppScript Expertise: Proven experience using Google AppScript for enterprise automation or custom add-ons. API Design: Deep understanding of RESTful APIs and asynchronous programming. Experience in end to end agentic workflows Strong experience in using Gen AI technologies : Gemini, co-pilot, claude AI Benefits Professional training programs Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row

🏢 Summary: Remote Senior FullStack Developer role focused on building and scaling end-to-end AI applications with agentic workflows and intuitive front-end interfaces. The position involves designing AI-driven optimizations, integrating LLM-based systems, and developing data-heavy backend services. The role requires close collaboration with stakeholders to translate complex requirements into production-ready solutions. 🗂️ Requirements: Minimum 5 years of experience with Python (Django, Flask, or FastAPI), Experience building data-heavy or AI-integrated applications, Strong proficiency in Vanilla JavaScript, Hands-on experience with AngularJS and knowledge of migration to modern Angular, Experience building agentic AI systems based on LLMs, Practical knowledge of LangChain, LlamaIndex, RAG, and AI orchestration frameworks, Commercial cloud experience with GCP or AWS, Proven experience with Google AppScript for enterprise automation, Strong understanding of RESTful APIs, Experience with asynchronous programming, Experience designing end-to-end agentic workflows, Hands-on experience with Generative AI tools such as Gemini, Copilot, or Claude 📃 Skills: Python, Django, Flask, FastAPI, JavaScript, AngularJS, Angular, LangChain, LlamaIndex, RAG, LLM, GCP, AWS, AppScript, REST, Gemini, Copilot, Claude 🏢 Description: This is a remote position. As a Senior FullStack Developer at Virtusa , you will build and scale end-to-end AI applications, integrate automated workflows, and design intuitive front-end interfaces. You will diagnose architectural bottlenecks, propose AI-driven optimizations, and communicate directly with stakeholders to turn complex requirements into functional code. This is a fully remote project within Poland. Requirements At least 5 years of experience with Python (Django, Flask, or FastAPI), specifically for data-heavy or AI-integrated applications. Strong mastery of Vanilla JavaScript and hands-on experience with Angular JS (and familiarity with the migration path to modern Angular). Hands-on experience building agentic AI systems and autonomous workflows based on LLMs. Strong practical knowledge of: LangChain, LlamaIndex, RAG, AI agent orchestration frameworks. Commercial cloud experience: GCP (preferred) or AWS AppScript Expertise: Proven experience using Google AppScript for enterprise automation or custom add-ons. API Design: Deep understanding of RESTful APIs and asynchronous programming. Experience in end to end agentic workflows Strong experience in using Gen AI technologies : Gemini, co-pilot, claude AI Benefits Professional training programs Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row

🏢 Summary: The offer is for a backend-focused AI Engineer role building a modern AI platform for business process automation and multi-agent system integration in a production-grade enterprise environment. The position centers on developing scalable Python-based services, secure API integrations, and cloud-native AI solutions using LLMs and RAG. The role involves designing robust, secure, and scalable architectures deployed on AWS or Azure with containerized infrastructure. 🗂️ Requirements: Extensive experience in backend development with Python in production environments, Hands-on experience with AI Agents, RAG, MCP, or LLM-based solutions, Experience with system integrations and API architecture, Experience with scalable cloud-based applications, Experience with AWS or Azure, Experience with Docker and Kubernetes, Experience designing secure and scalable enterprise solutions, Experience with multi-agent systems and workflow automation, Ability to conduct code reviews and mentor developers, Fluent English and Polish 📃 Skills: Python, LLM, RAG, MCP, AWS, Azure, Docker, Kubernetes, API, Microservices, Cloud, AI, Agents 🏢 Description: Additional information The project focuses on building and developing a modern AI platform supporting business process automation and the integration of intelligent agents with enterprise systems. The team is creating scalable solutions based on Python, cloud technologies, and multi-agent architecture, leveraging technologies such as LLMs, RAG, and advanced workflow automation. A key aspect of the project is designing secure integrations between AI platforms, internal systems, and external APIs within a production-grade environment. The project is delivered in an international technology-driven environment with a strong focus on innovation, high-quality architecture, and the development of cutting-edge AI solutions for a global industrial organization. You’re ideal for this role if you: Have extensive experience in backend development with Python in production environments Have hands-on experience with AI technologies such as AI Agents, RAG, MCP, or LLM-based solutions Understand system integrations, API architecture, and scalable cloud-based applications Have worked with AWS or Azure and containerized environments such as Docker and Kubernetes Are experienced in designing secure and scalable enterprise solutions Have strong problem-solving skills and can proactively remove technical blockers Enjoy working closely with cross-functional teams in an international environment Have experience mentoring developers, conducting code reviews, and promoting engineering best practices Are interested in modern AI architectures, workflow automation, and multi-agent systems Communicate fluently in English and Polish and feel comfortable working in a global setup Your day-to-day responsibilities include:​ Designing and developing scalable backend services and AI-driven integration solutions in Python Building and maintaining APIs, connectors, and middleware between AI platforms and enterprise systems Creating and optimizing multi-agent workflows and intelligent automation processes Collaborating with AI Engineers, Data Engineers, and other technical stakeholders on system architecture and integrations Integrating external AI platforms, internal tools, and cloud services into production environments Working with cloud technologies and containerized infrastructure in AWS or Azure environments Improving the quality, reliability, and performance of AI-powered solutions and LLM-based workflows Conducting code reviews, mentoring team members, and supporting engineering best practices Troubleshooting technical issues, identifying bottlenecks, and driving continuous improvements Contributing to technical documentation, architecture discussions, and innovation initiatives across the team