Senior Python AI Engineer (green building)

🏢 Summary: Oferta dotyczy roli inżyniera AI/LLM odpowiedzialnego za projektowanie i wdrażanie produkcyjnych systemów opartych na Pythonie oraz zaawansowanych architekturach LLM. Stanowisko obejmuje budowę rozwiązań RAG, orkiestrację agentów oraz przygotowanie pipeline’ów danych pod modele językowe. Rola wymaga pracy z wektorowymi bazami danych oraz zapewnienia jakości poprzez testy i ewaluację systemów niedeterministycznych. 🗂️ Requirements: Minimum 3 lata komercyjnego doświadczenia w projektowaniu i wdrażaniu systemów produkcyjnych w Pythonie, Doświadczenie w budowie zaawansowanych architektur LLM (RAG, harness engineering, orkiestracja), Praktyczna znajomość LangChain lub LlamaIndex, Znajomość wzorców projektowych i zasad Clean Code, Doświadczenie w pisaniu testów i ewaluacji systemów niedeterministycznych, Doświadczenie w Data Engineering dla LLM (ETL, parsowanie dokumentów, chunking, transformacje danych), Praca z bibliotekami do manipulacji danymi, Znajomość wektorowych baz danych i strategii chunkingu, Wykształcenie wyższe w kierunku ścisłym lub pokrewnym, Znajomość języka angielskiego na poziomie min. B2 📃 Skills: Python, LLM, RAG, LangChain, LlamaIndex, Pandas, NumPy, Qdrant, Pinecone, Chroma, ETL, Azure, GCP, AWS, Docker, Kubernetes, PyTorch, TensorFlow, C#, Go, Java, SQL, AzureDevOps 🏢 Description: Wymagania: Doświadczenie komercyjne: minimum 3 lata projektowania i wdrażania systemów w jakości produkcyjnej w Pythonie. Udokumentowane doświadczenie w budowaniu zaawansowanych architektur LLM: zaawansowany RAG, harness engineering oraz orkiestracja przy użyciu frameworków takich jak LangChain lub LlamaIndex. Znajomość wzorców projektowych, zasad Clean Code oraz pisania testów i ewaluacji dla systemów niedeterministycznych. Doświadczenie w Data Engineering pod LLM: ETL dla danych nieustrukturyzowanych (parsowanie dokumentów, chunking), transformacji oraz pracy z bibliotekami manipulacji danymi (Pandas, NumPy). Praktyczna znajomość wektorowych baz danych (np. Qdrant, Pinecone, Chroma) oraz strategii chunkingu i zarządzania metadanymi. Umiejętność przekładania skomplikowanych koncepcji AI na język korzyści biznesowych i współpraca z zespołami produktowymi. Wyższe wykształcenie (lub w trakcie) w naukach ścisłych/ilościowych (Informatyka, Matematyka, Fizyka, Ekonometria lub pokrewne) oraz znajomość języka angielskiego na poziomie min. B2. Welcome Skills: Znajomość zaawansowanych frameworków agentowych: LangGraph, CrewAI, AutoGen. Praktyka z chmurami (Azure, GCP lub AWS) oraz konteneryzacją i orkiestracją (Docker, Kubernetes). Zrozumienie klasycznego NLP oraz frameworków głębokiego uczenia (PyTorch, TensorFlow) na potrzeby utrzymania i aktualizacji istniejących komponentów. Znajomość dodatkowego języka (C#, Go, Java). Szczególnie cenimy komercyjne doświadczenie w ekosystemie .NET (C#, SQL Server, Azure PaaS) oraz budowaniu potoków CI/CD (Azure DevOps).

🏢 Summary: Mid–Senior Python Backend Developer role focused on designing and maintaining scalable backend services, RESTful APIs, and microservices in cloud environments. The position emphasizes Microsoft Azure-based solutions, CI/CD automation, and containerized deployments using Docker and Kubernetes. You will work in an Agile team to deliver secure, high-performance cloud-native applications. 🗂️ Requirements: Commercial experience as Python Backend Developer (mid–senior level), Strong experience with Python, Hands-on experience with Microsoft Azure (App Services, Functions, AKS, Storage), Experience with FastAPI and/or Django, Experience designing RESTful APIs, Experience with microservices architecture, Knowledge of CI/CD pipelines and automated testing, Production experience with Docker and Kubernetes, Knowledge of SQL and NoSQL databases, Understanding of cloud architecture patterns and scalability, Proficiency with Git 📃 Skills: Python, Azure, FastAPI, Django, REST, Microservices, CI/CD, Docker, Kubernetes, SQL, NoSQL, Git, GCP, Databricks, Golang, React, Terraform, Bicep, ARM, Kafka, ServiceBus 🏢 Description: Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics. Tasks: Design, develop, and maintain backend services using Python . Build and optimize RESTful APIs and microservices . Work with Microsoft Azure (priority) to design, deploy, and manage cloud solutions. (Experience with GCP is acceptable as an alternative.) Implement CI/CD pipelines and automated testing workflows. Work with Docker and Kubernetes in production environments. Collaborate in an Agile/Scrum team and participate in code reviews, planning, and architecture discussions. What We're Looking For: Strong commercial experience as a Python Backend Developer (mid–senior level). Hands‑on experience with Azure (App Services, Functions, AKS, Storage, etc.). Experience with FastAPI and/or Django . Proven experience designing RESTful APIs and scalable microservice architectures. Solid understanding of CI/CD , automated testing, and deployment pipelines. Proficiency with Docker and Kubernetes in production. Comfortable working in English and collaborating in cross‑functional teams. Additional Expected Skills: Strong knowledge of SQL/NoSQL databases and data modeling. Understanding of cloud architecture patterns, scalability, and performance optimization. Familiarity with unit, integration, and end‑to‑end testing practices. Proficiency with Git and collaborative development workflows. Awareness of security best practices in cloud and backend environments. What Will Set You Apart: Experience with Databricks or other big‑data/data engineering platforms. Commercial experience with Golang . Full‑stack skills , especially with React. Experience with Infrastructure as Code tools (Terraform, Bicep, ARM templates). Knowledge of event‑driven architectures and messaging systems (Kafka, Azure Service Bus, etc.). Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow. We offer: Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites. “Office as an option” model. You can choose to work remotely or in the office. Workation. Enjoy working from inspiring locations in line with our workation policy. Great Place to Work® certified employer. Flexibility regarding working hours and your preferred form of contract. Comprehensive online onboarding program with a “Buddy” from day 1. Cooperation with top-tier engineers and experts. Unlimited access to the Udemy learning platform from day 1. Certificate training programs. Lingarians earn 500+ technology certificates yearly. Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. Grow as we grow as a company. 76% of our managers are internal promotions. A diverse, inclusive, and values-driven community. Autonomy to choose the way you work. We trust your ideas. Create our community together. Refer your friends to receive bonuses. Activities to support your well-being and health. Plenty of opportunities to donate to charities and support the environment. Modern office equipment. Purchased for you or available to borrow, depending on your location.

🏢 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

🏢 Summary: Python AI Engineering role focused on building production-grade GenAI, RAG, and agentic systems for client engagements. The position involves end-to-end ownership of AI solutions, including architecture, delivery, evaluation, and client communication in a fast-paced consulting environment. Candidates will work with scalable APIs, LLM pipelines, and cloud AI services while ensuring quality, observability, and performance. 🗂️ Requirements: 5+ years commercial Python experience, 3+ years hands-on GenAI/LLM engineering, Experience building scalable services and APIs, Experience with FastAPI, Flask, or Django, Experience writing test suites with pytest, Experience building RAG pipelines, Knowledge of embeddings and vector search, Experience with agentic workflows and tool-calling, Strong prompt engineering skills, Experience with structured outputs and JSON schemas, Experience with Pydantic or equivalent, Experience with AWS, Azure, or GCP, Understanding of managed AI/ML services, Ability to evaluate relevance, latency, consistency, and cost, High-proficiency written and spoken English 📃 Skills: Python, GenAI, LLM, FastAPI, Flask, Django, pytest, RAG, Embeddings, VectorSearch, ToolCalling, PromptEngineering, JSON, Pydantic, Instructor, AWS, Azure, GCP, Bedrock, OpenAI, LangGraph, LangSmith, LlamaIndex, Pinecone, Weaviate, Milvus, pgvector 🏢 Description: We're growing our Python AI Engineering team - the group that builds GenAI systems clients actually run, not proof-of-concepts that die after the demo. Expect real agentic/RAG systems, real users, and evaluation data that tells you whether what you built actually works. Depending on fit and timing, you'll be matched to one of several active or upcoming client engagements - each with its own domain, constraints, and stack, but the same bar for engineering quality. You are a good fit for the role if... You default to shipping, not just designing - a proactive, "getting things done" attitude in a fast-paced, client-facing setup where the interesting problems rarely come pre-scoped in a ticket. You own the AI lifecycle end to end - ideation, architecture, delivery, evaluation - and you're comfortable being the technical voice in the room: proposing the approach, defending it with data (evals, latency, cost), and adjusting it when the data says you're wrong. You can translate engineering constraints into terms a client stakeholder acts on - not just "this won't scale" but why, what the tradeoff actually costs them, and what a workable alternative looks like. Good technical judgment shows up as much in how you explain a constraint as in identifying it. You treat client pushback as a design input, not an obstacle - sometimes it reveals a real business constraint you were missing, sometimes it's a shortcut worth resisting. Telling those two cases apart, and being able to argue either side with evidence, is the actual skill. Our expectations 5+ years commercial Python experience, including 3+ years of hands-on GenAI/LLM engineering. Solid engineering fundamentals: building scalable services/APIs (FastAPI, Flask, or Django), writing real test suites (pytest), clean and modular architecture. Hands-on experience building RAG pipelines - retrieval, embeddings, vector search. Working knowledge of agentic patterns: tool-calling, function-calling, multi-step reasoning workflows. Strong prompt engineering skills, including structured outputs (JSON schemas, Pydantic, Instructor or equivalent). Experience with at least one major cloud platform (AWS, Azure, or GCP), including its managed AI/ML services (e.g., Bedrock, Azure OpenAI). An "evals mindset" - you think about relevance, consistency, latency, and cost as real engineering concerns, not afterthoughts. High-proficiency written and spoken English - you'll use it daily with clients and teammates. Welcome Skills Experience with orchestration frameworks beyond the basics - LangGraph, LangSmith, LlamaIndex. Hands-on with a specific vector database (Pinecone, Weaviate, Milvus, pgvector) beyond "I integrated one once." Experience building evaluation frameworks or golden-dataset pipelines specifically (as opposed to just using one). Exposure to data pipeline work feeding AI systems - understanding how data quality/freshness affects model behavior. Prior client-facing / consulting experience in a professional-services or consulting setup. Key tasks Design and build Python services and APIs that wrap LLM-powered functionality. Build and maintain agentic and RAG pipelines: retrieval, reranking, tool-calling, multi-step reasoning, structured outputs. Care about quality beyond "it works" - evals, observability, and the data that tells you when something regresses. Work directly with clients: translate fuzzy business requirements into architecture decisions, and explain your technical tradeoffs to non-technical stakeholders. Work across a distributed, multi-market team and client organizations.

🏢 Summary: Senior Python Engineer role focused on building AI-powered products and internal platforms using Python and modern cloud technologies. The position involves developing secure, production-grade backend systems, contributing to frontend components, and implementing AI-driven solutions such as agentic systems and vector search. Work is delivered in agile teams with strong emphasis on cloud-native architecture and high engineering standards. 🗂️ Requirements: Bachelor’s or Master’s degree in technical field, 7+ years software development experience, Senior-level experience in large tech environment, Strong Python backend experience, Production experience with FastAPI, Hands-on experience with cloud platforms, Experience with Docker or Kubernetes, Experience with SQL and NoSQL databases, Experience with messaging queues, Practical experience with AI systems in production 📃 Skills: Python, FastAPI, Django, Vue, React, Angular, Svelte, AWS, Azure, GCP, Docker, Kubernetes, SQL, NoSQL, Pinecone, CrewAI, MCP, A2A, Microservices 🏢 Description: We’re looking for a Senior Python Engineer to help build AI‑powered products and internal platforms used across the company. You’ll join a fast‑moving engineering team where AI accelerates development, improves productivity, and shapes how new solutions are delivered. Security, compliance, and high engineering standards are essential, especially for production systems handling sensitive data. What you’ll do Build end‑to‑end features using Python (FastAPI, Django) as your primary backend stack. Contribute to frontend development when needed — experience with Vue is a plus, but React, Angular, or Svelte are also welcome. Develop cloud‑native systems on AWS, Azure, or GCP, working with containers, databases, and messaging systems. Contribute to AI initiatives, including agentic systems, vector search, and prompt‑driven workflows. Work in small, agile squads with the flexibility to move between projects as priorities evolve. Required qualifications Bachelor’s or Master’s degree in a technical field. At least 7 years of software development experience, including senior‑level work in a large tech environment. Strong backend experience with Python and FastAPI, with proven production delivery. Frontend experience is a plus (Vue preferred, but any modern JavaScript framework is welcome). Hands‑on experience with cloud platforms, Docker or Kubernetes, SQL and NoSQL databases, and messaging queues. Practical experience working with AI systems or AI‑driven features in production environments. Preferred qualifications Experience with vector databases such as Pinecone or Azure AI Search. Knowledge of prompt engineering, context management, and LLM‑driven workflows. Experience with agentic AI frameworks such as CrewAI, Microsoft Agent Framework, or AWS Agent Core. Familiarity with agentic protocols like A2A or MCP. Background in distributed systems and microservices. Experience working in agile teams. Understanding of agentic AI concepts or hands‑on exposure to agent‑based architectures. Strong grasp of engineering best practices, design patterns, and secure coding. Clear communication skills and the ability to explain technical concepts.

🏢 Summary: Oferta dotyczy roli Senior Python Developera odpowiedzialnego za budowę i wdrażanie produkcyjnej warstwy aplikacyjnej wokół rozwiązań Data Science i GenAI w architekturze mikroserwisowej. Rola obejmuje projektowanie aplikacji Python, produkcjonalizację rozwiązań LLM/RAG, wdrożenia na Kubernetes/OpenShift oraz rozwój standardów architektonicznych i CI/CD. Kandydat będzie współpracować z zespołami Data Science i bezpieczeństwa oraz wspierać rozwój dobrych praktyk programistycznych. 🗂️ Requirements: Minimum 5 lat komercyjnego doświadczenia w Python, Doświadczenie jako technical leader lub senior developer, Bardzo dobra znajomość FastAPI, Doświadczenie w projektowaniu systemów i mikroserwisów, Znajomość REST i architektury event-driven, Znajomość Kafka, Znajomość data/AI stack, Doświadczenie z projektami LLM/RAG, Znajomość vLLM, Znajomość LangChain, Znajomość LlamaIndex, Znajomość LangGraph, Praktyczna znajomość Docker, Znajomość Kubernetes lub OpenShift, Doświadczenie z CI/CD, Doświadczenie z GitLab lub ADO, Praktyka w pisaniu testów, Bardzo dobra znajomość Git, Doświadczenie w code review, Umiejętność współpracy z zespołem Data Science, Dyscyplina dokumentacyjna, Znajomość observability i monitoringu, Znajomość zasad cyberbezpieczeństwa, Znajomość podatności aplikacji webowych i API, Doświadczenie z uwierzytelnianiem i autoryzacją, Znajomość języka polskiego na poziomie B2 📃 Skills: Python, FastAPI, Pydantic, REST, Kafka, Airflow, Spark, Iceberg, MsSQL, Oracle, S3, LLM, RAG, vLLM, LangChain, LlamaIndex, LangGraph, Docker, Podman, Kubernetes, OpenShift, Helm, Tekton, ArgoCD, GitLab, ADO, pytest, Git, Prometheus 🏢 Description: Dla naszego klienta, lidera branży paliwowo-energetycznej, szukamy Senior Python Developera, który wesprze działania zespołu w fazie budowania i wdrożenia produkcyjnej warstwy aplikacyjnej wokół rozwiązań Data Science i GenAI. Our expectations Minimum 5 lat komercyjnego doświadczenia w produkcyjnym programowaniu w Python jako technical leader lub senior developer. Bardzo dobra znajomość FastAPI ( m.in . async, Pydantic, dependency injection, obsługa błędów) Doświadczenie w projektowaniu systemów i mikroserwisów (FE, BE, API, REST, event-driven, Kafka ) Znajomość data/AI stack (np. Airflow, Spark, Iceberg, Kafka, MsSQL, Oracle, S3 storage) Doświadczenie w co najmniej jednym produkcyjnym projekcie z LLM / RAG (orkiestracja zapytań, integracja z modelem, vector store, ewaluacja, kontrola kosztów / latencji) oraz znajomość rozwiązań takich jak vLLM, LangChain, LLamaIndex, LangGraph Praktyczna znajomość Dockera i Podmana(dodatkowy plus) oraz Kubernetes/OpenShift ( m.in . deploymenty, configmap/ secerts, probes, resource limits, Helm, routes itp.) Doświadczenie z CI/CD (gotowość do pracy z Tektonem + ArgoCD, GitLab, ADO) Praktyka w pisaniu testów (pytest, testy jednostkowe, integracyjne) Bardzo dobra znajomość Git i pracy w trybie code review, Umiejętność współpracy z osobami o profilu data science, także w zakresie wsparcia merytorycznego. Dyscyplina dokumentacyjna, m.in . opisy API, README, decyzje architektoniczne Observability: strukturalne logowanie, metryki np. Prometheus Samodzielność i proaktywność Znajomość zasad cyberbezpieczeństwa - od projektu, przez kod po wdrożenie Znajomość typowych podatności aplikacji webowych i API oraz zagrożeń specyficznych dla aplikacji opartych o LLM Bezpieczna komunikacja mikroserwisów (w tym bezpieczeństwo API) Bezpieczne pakowanie i orkiestracja kontenerów Doświadczenie z uwierzytelnianiem i autoryzacją w aplikacjach na poziomie pozwalającym poprawnie wdrażać te mechanizmy w mikroserwisach. Znajomość języka polskiego pozwalająca na swobodną komunikację (mi.n poziom B2) Welcome Skills Znajomość języka angielskiego (min. B2) Key tasks Projektowanie i implementacja aplikacji w Pythonie w architekturze mikroserwisowej Produkcjonalizacja rozwiązań przygotowanych przez zespół Data Science (np. aplikacje typu RAG, serwisy udostępniające klasyczne modele ML) Współtworzenie oraz utrzymywanie standardów i wzorców architektonicznych dla zespołu (template’y serwisów, konwencje API, podejście do testów, CI/CD) Wdrażanie aplikacji na platformie Openshift / Kubernetes z wykorzystaniem firmowego pipeline’u CI/CD (docelowo Tekton + ArgoCD) Współpraca z zespołem bezpieczeństwa w zakresie wdrożeń, dostępów, polityk i przeglądów bezpieczeństwa Code review dla pull requestów członków zespołu DS Pair programming, w szczególności przy bardziej złożonych komponentach inżynierskich Prowadzenie wewnętrznych mini-szkoleń i sesji wiedzy w zakresie dobrych praktyk Python developementu, mikroserwisów i bezpieczeństwa aplikacji Dokumentacja ( m.in . ADR, kontrakt API)

🏢 Summary: Senior Python Engineer role focused on building and deploying enterprise-grade, AI-powered solutions in a cloud-based microservices environment for a large-scale professional services project. The position involves end-to-end development of scalable Python applications, integration of Generative AI and LLM capabilities, and technical leadership within a cross-functional team. Offered as a remote B2B contract with a competitive hourly rate. 🗂️ Requirements: 5+ years of commercial experience in software development, Strong hands-on experience with Python and FastAPI, Practical knowledge of Pydantic for schema modelling and data validation, Experience with asyncio and asynchronous/parallel programming, Experience with Generative AI and Large Language Models in real business use cases, Understanding of RAG pipelines and hybrid search with vector databases, Strong analytical and problem-solving skills, Very good organizational and self-management skills, Strong troubleshooting and communication skills, English level Intermediate+ 📃 Skills: Python, FastAPI, Pydantic, asyncio, LLM, RAG, LangChain, LangGraph, Azure, MongoDB, AzureSQL, Angular, Kendo, GitHub, Copilot, Docker, Kubernetes, .NET, ASP.NET, Microservices 🏢 Description: For our client we are looking for an experienced Senior Python Engineer to join a modern technology initiative delivered for one of the Big Four firms - the world's largest professional services network, headquartered in London and operating across more than 150 countries. The team behind this project is responsible for designing, building, and deploying enterprise-grade tools and AI-powered solutions that support tax service delivery. It is a cross-functional environment bringing together experts in software engineering, tax, project management, and change management. The scope of work includes solution design, implementation, rollout, training support, and broader stakeholder collaboration. Tech stack Azure Cloud, Microservices Architecture, .NET 8, ASP.NET Core services, Python, MongoDB, Azure SQL, Angular 18, Kendo, GitHub Enterprise with Copilot, LangGraph, LangChain, RAG Pipelines, Multi-modal LLMs Responsibilities Analyse business and technical requirements, contribute to system design, and support end-to-end Python and AI solution development Build, enhance, and maintain scalable Python applications using FastAPI and Pydantic Develop asynchronous and parallel processing solutions with asyncio Perform detailed code reviews to ensure consistency with engineering standards and maintain high code quality Integrate and test multi-modal GenAI capabilities, including areas such as text-to-image and text-to-audio Work effectively both independently and as part of a collaborative team Support day-to-day team coordination by giving clear guidance and helping organize ongoing work Stay in regular contact with the client and support smooth communication Provide technical leadership within the team by mentoring others, coaching colleagues, and setting a strong example Requirements 5+ years of commercial experience in software development Strong hands-on experience with Python and FastAPI Good practical knowledge of Pydantic for schema modelling and data validation Experience with asyncio and asynchronous / parallel programming Practical experience with Generative AI and Large Language Models, including building agentic AI solutions for real business use cases Good understanding of RAG pipelines and hybrid search with vector databases Strong analytical thinking and problem-solving skills, with close attention to detail Pragmatic mindset and the ability to balance process, structure, and flexibility in delivery Very good organizational skills, including self-management, prioritization, and effective work under deadlines Strong troubleshooting and communication skills English level: Intermediate+ Nice to have Experience with Azure Cloud services or other major cloud platforms, including SaaS tools such as Service Bus, Data Lake, Blob Storage, Redis, and similar solutions Familiarity with agentic protocols such as MCP and A2A Hands-on experience with the LangGraph ecosystem, especially long-term memory, state management, and human-in-the-loop workflows Familiarity with .NET Experience with Docker and Kubernetes Solid understanding of microservices architecture and scalable distributed systems Offer rate: 140 - 160 pln B2B remote

🏢 Summary: The offer is for a Senior Python Backend Engineer to design and maintain scalable, cloud-native backend systems on AWS, including REST APIs and AI/LLM integrations. The role focuses on distributed systems, asynchronous processing, observability, and high code quality within a modern CI/CD environment. It involves working with both serverless and containerized deployments in a collaborative, agile team. 🗂️ Requirements: 3–5+ years of professional Python backend development experience, Experience building cloud-native systems on AWS, Strong knowledge of REST API design and OpenAPI, Experience with asynchronous processing and queue-based architectures, Hands-on experience with core AWS services (Lambda, API Gateway, S3, IAM, ECS/EKS, CloudWatch), Knowledge of DynamoDB and NoSQL data modelling, Knowledge of PostgreSQL, SQL, and relational data modelling, Experience with serverless and containerized deployments, Experience integrating external APIs and third-party services, Experience with automated testing using pytest, Familiarity with CI/CD tools, Understanding of distributed systems, scalability, and reliability, Practical understanding of LLM-based or AI-driven applications, Ability to apply SOLID principles and clean code practices, Fluent English (written and spoken) 📃 Skills: Python, AWS, FastAPI, Pydantic, SQLAlchemy, boto3, REST, OpenAPI, Celery, SQS, Lambda, ECS, EKS, S3, CloudFront, IAM, SecretsManager, CloudWatch, DynamoDB, PostgreSQL, SQL, pytest, GitHubActions, Jenkins, NewRelic, Docker, Kubernetes, LLM, Cursor, Claude, Copilot 🏢 Description: We are looking for a Senior Python Backend Engineer with experience in building cloud-native backend systems on AWS. This role is focused on designing, developing, and maintaining scalable Python services, integrating AI/LLM-based capabilities, working with distributed systems, and ensuring high reliability, observability, and code quality. Your responsibilities: Design, build, and maintain backend services using Python in an AWS-based environment. Develop and maintain REST APIs together with clear OpenAPI documentation. Implement asynchronous processing and queue-based communication between services. Design data access patterns for application features using NoSQL and SQL storage. Integrate backend services with internal systems, external APIs, and AI/LLM-based components. Implement reliable communication patterns, including retries, timeouts, and circuit breakers. Build and maintain operational CLI tooling for day-to-day platform tasks (e.g. content ingestion). Contribute to architectural decisions across software and infrastructure as the stack evolves. Create observability for distributed systems, including logging, metrics, tracing, and alerting. Write automated tests and support high code quality across the backend codebase. Contribute to CI/CD processes and deployment automation. Collaborate with product, frontend, QA, DevOps, AI/ML teams, and content creators. Review code, share knowledge, and raise the bar for engineering practice across the team. We are looking for you, if you have: 3–5+ years of professional experience in Python backend development. Solid understanding of REST API design and OpenAPI standards. Experience with asynchronous processing and queue-based architectures, e.g. Celery, SQS. Experience with libraries and frameworks such as FastAPI, Pydantic, SQLAlchemy, boto3. Hands-on experience with core AWS services such as Lambda, API Gateway, S3, CloudFront, Secrets Manager, IAM, ECS/EKS, CloudWatch, etc. Good knowledge of DynamoDB and NoSQL data modelling. Good knowledge of PostgreSQL, SQL, and relational data modelling . Experience with both serverless (Lambda) and containerized (ECS/EKS) deployment models. Experience integrating with external APIs and third-party services. Experience with pytest and automated testing practices. Familiarity with CI/CD tools such as GitHub Actions and/or Jenkins. Experience with observability tools such as New Relic and CloudWatch. Understanding of distributed systems, scalability, reliability, and fault tolerance. Ability to apply SOLID principles, clean code practices, and common design patterns. Practical understanding of LLM-based applications or AI agentic frameworks. Ability to use AI development tools such as Cursor, Claude Code, or GitHub Copilot. Experience working in agile software development teams. Fluent English, both written and spoken. We offer: Participation in interesting and demanding projects. Flexible working hours. A great, non-corporate atmosphere. Possibility to work remote or hybrid (2 days per week from the office). Opportunities for development and promotion. Attractive package of benefits. We reserve the right to contact the selected candidates.

🏢 Summary: Python Developer role focused on building backend systems and AI/LLM integrations, starting with an open-source AI Red Teaming platform. The position involves developing a modular Python backend with integrations to major AI providers, real-time streaming, evaluation engines, analytics, and AWS deployment. Work includes commercial and open-source projects for international clients. 🗂️ Requirements: 3+ years commercial experience in Python backend development, Experience with Django, FastAPI, or Flask, Experience integrating AI/LLM APIs (e.g. OpenAI, Anthropic), Strong knowledge of PostgreSQL, Experience designing REST APIs, Experience with asynchronous programming in Python, Experience with Docker, Experience with CI/CD pipelines, Experience writing automated tests, Good command of English, Degree in Computer Science or related field 📃 Skills: Python, Django, FastAPI, Flask, PostgreSQL, REST, AsyncIO, Docker, CI/CD, OpenAI, Anthropic, Gemini, AWS, EKS, S3, RDS, WebSockets, SSE, LiteLLM 🏢 Description: We're looking for a Python Developer to join our team and work across a range of commercial and open-source projects focused on Python backend development and AI/LLM solutions. You'll build backends, design integrations with AI model providers, and contribute to products used by international clients. Project description: Your first project will be developing a Python-based backend for an open-source AI Red Teaming platform - a tool that enables organizations to systematically test and evaluate AI/LLM models for safety, fairness, and reliability. The project involves building a modular backend with integrations to major AI model providers (OpenAI, Anthropic, Google Gemini, AWS Bedrock, and others), real-time streaming, evaluation engine, analytics, and deployment on AWS. The platform will be released as an open-source product with a separate managed instance for the client. Requirements: - 3+ years of commercial experience in Python backend development - Experience with at least one modern Python web framework (Django, FastAPI, or Flask) - Practical experience integrating AI/LLM APIs into applications (e.g. OpenAI, Anthropic, or similar providers) - Solid knowledge of PostgreSQL and REST API design - Familiarity with async programming in Python - Experience with Docker and CI/CD pipelines - Experience writing automated tests - Good command of English (daily communication with an international client) - Degree in computer science or a related field Nice to have: - Experience with FastAPI - Experience with LiteLLM or similar LLM abstraction/routing libraries - Experience with real-time streaming (SSE, WebSockets) - Experience with AWS services (EKS, S3, RDS) - Familiarity with React or frontend technologies - Experience with open-source projects What We Offer - Fully remote work within a small, supportive team - Real responsibility from the start - no months of onboarding before you contribute - Variety - multiple projects mean diverse problems and technologies - Opportunities for professional growth, including contributions to open-source projects - A team culture built on transparency, trust, and fast feedback We look forward to hearing from you!

🏢 Summary: The role focuses on engineering production-grade AI features such as semantic search, intelligent assistants, and automated risk scoring by integrating external AI providers into a cybersecurity platform. You will own the full lifecycle from prototype to reliable, monitored production services, primarily using Python on Azure. This position emphasizes robust software engineering practices over model research or training. 🗂️ Requirements: 5+ years of professional experience building production systems in Python, Expert-level Python programming skills, Experience with ML frameworks and libraries, Proven experience shipping and operating production software, Experience integrating external APIs in production environments, Strong understanding of software architecture and design patterns, Practical experience with CI/CD pipelines, Experience with containerization using Docker, Understanding of AI/ML concepts including LLMs, embeddings, prompt engineering, RAG, Experience with unit and integration testing and mocking external services, Polish work permit, Professional proficiency in English 📃 Skills: Python, Azure, OpenAI, Anthropic, Docker, CI/CD, FastAPI, Flask, Pinecone, Weaviate, Chroma, .NET, REST, LLMs, RAG, Embeddings, Git 🏢 Description: About the Role As a Senior AI/ML Engineer you will be building AI-powered features at the core of our platform - semantic search, an intelligent assistant, automated risk scoring, and much more. We mainly integrate with external AI model providers (OpenAI, Anthropic, and others) to deliver these capabilities to our clients and internal users. This is a software engineering role, not a data science or ML research position. You won't train models from scratch or publish papers. You'll engineer production-grade systems that leverage AI to solve real cybersecurity problems. If you're a strong Python engineer excited about making AI reliable, maintainable, and impactful — we want to talk to you. We're looking for a versatile software engineer to own the journey from AI prototype to reliable production system: building robust integrations with external AI providers or fine-tuned models, standardizing our Python codebase and release pipelines, and ensuring our AI features meet the same quality bar as any other production service. What You'll Do Ship AI features end to end - from integration design through deployment to monitoring in production. You'll build and maintain Python services that power our AI-driven capabilities on Azure. Build production-ready AI / ML integrations - including retry logic, rate limiting, cost monitoring, fallback strategies, and abstraction layers that allow us to swap between model providers. Turn proofs of concept into reliable software - collaborate with our AI experts (who bring deep ML/data science expertise) to take working prototypes and engineer them into tested, documented, production-grade services. Standardize Python engineering practices - establish and evolve our code organization, testing strategies, CI/CD pipelines, and release processes for AI/ML features. Design clean service boundaries - our platform's core runs on .NET. You'll design and maintain well-defined APIs between the Python/AI layer and the rest of the system. Mentor and share knowledge - help other engineers grow their Python and AI engineering skills, and bring engineering rigor to the broader team's practices. Contribute to architecture decisions - work closely with other teams to shape how AI capabilities evolve within the platform. Who You Are Must-Haves 🔹 5+ years of professional experience building and maintaining production systems in Python. 🔹 Expert-level programming skills and proficiency with common ML frameworks and libraries. 🔹 A track record of shipping and operating software - not just building prototypes. You care about testing, monitoring, logging, and what happens after deployment. 🔹 Experience integrating external APIs in production systems - ideally AI/LLM provider APIs (OpenAI, Anthropic, Azure AI, or similar), but strong API integration experience in any domain counts. 🔹 Solid understanding of software architecture and design patterns - you have opinions about how to structure a Python project and can articulate trade-offs. 🔹 Practical knowledge of CI/CD pipelines, containerization (Docker), and modern development workflows. 🔹 A working understanding of AI/ML concepts - you know what embeddings, LLMs, prompt engineering, and RAG are. You can have a productive technical conversation with an ML specialist without needing every concept explained from scratch. 🔹 Experience with testing strategies - unit tests, integration tests, mocking external services. You instinctively write tests, not as an afterthought. 🔹 A highly adaptable, problem-solving and result-oriented mindset with the ability to work independently and take ownership in a fast-paced and dynamic environment. 🔹 Strong communication skills in English (our working language). 🔹 Willingness to learn continuously and share what you learn with the team. Nice-to-Haves 🔸 Experience with Azure cloud services. 🔸 Familiarity with FastAPI, Flask, or similar Python web frameworks. 🔸 Exposure to MLOps tooling or practices (model versioning, experiment tracking, feature stores). 🔸 Hands-on experience in Document AI / Intelligent Document Processing using traditional models and Generative AI. 🔸 Experience with vector databases (Pinecone, Weaviate, Chroma, or similar). 🔸 Any experience with .NET - helpful for cross-team collaboration, but not expected. 🔸 Background in or interest in cybersecurity as a domain. Your Team You'll join our Synapse team - a small, focused group responsible for all AI/ML capabilities within our platform. The team consists of: -> Team Leader / Architect - provides high-level architectural guidance, planning, and cross-stack delivery. -> AI / ML Engineer - deep expertise in AI/ML and data science. Your counterbalance: they bring the ML knowledge, you bring the production engineering discipline. -> AI / Backend Engineer - transitioning from .NET into AI engineering. A teammate you'll mentor and grow alongside. -> You - the person who bridges the gap between AI prototypes and reliable production systems. Why Join Us? / What We Offer: Competitive salary and benefits package. Remote work options and flexible working hours. Actual impact on the choice and shape of solutions developed. Opportunities for professional growth and development. Training and conference budget. A collaborative, innovative work environment with an iterative agile approach. The role is for six months with the possibility of extension. Both full-time and part-time cooperation are possible.