Senior AI Engineer Warszawa Mazowieckie Poland

Job description

Industrialize and scale successful GenAI prototypes into secure, resilient IT products for Enabling Functions. Design, implement, and operate cloud-native APIs and microservices for AI workloads using Python and FastAPI, following schema-first design (OpenAPI/gRPC). Develop Model Context Protocol (MCP) servers (FastMCP) to safely expose enterprise tools and data to agents, ensuring robust permissions and auditing. Architect agent workflows with LangChain, LangGraph, and PydanticAI (tool calling, memory, event-driven orchestration). Build reliable text-to-sql solutions and/or RAG services with high-quality embeddings, indexing, reranking, and caching for performance and cost efficiency. Implement CI/CD pipelines (GitHub Actions) with automated testing. Deploy on AWS and/or Azure (containers, serverless, API gateways, managed databases, object storage, secrets). Ensure end-to-end observability: structured prompt/response logging with redaction, token/latency/cost tracking, OpenTelemetry tracing, and model/agent monitoring (e.g., Langfuse/LangSmith/MLflow). Establish safety and quality controls: evaluation pipelines, prompt/chain regression tests, content guardrails, and injection defenses. Collaborate across Data Science, MLOps/DevOps, Architecture, Product, and Business to align solutions with outcomes; contribute to stack decisions and cost/scalability trade-offs. Promote continuous learning via code reviews, tech talks, and mentoring on AI engineering best practices. Apply with confidence, we value potential over perfection! Master's degree (or equivalent) in Computer Science, Data/AI, Mathematics, or a related field; PhD is an advantage. 5+ years of professional experience in AI/software/ML engineering, with end-to-end product delivery in production environments. Advanced Python and production-grade API development (REST/gRPC), authN/authZ (OAuth2/OIDC), rate limiting. Containerization (Docker) expertise; Kubernetes experience is a plus. Proficiency in AWS and/or Azure: AWS (examples): Lambda, ECS/Fargate/EKS, API Gateway, S3, RDS, Secrets Manager, Bedrock. Azure (examples): Functions, AKS, API Management, Storage, PostgreSQL/Cosmos DB, Key Vault, Azure OpenAI. Strong CI/CD knowledge, especially GitHub Actions. Infrastructure as Code (Terraform preferred) Solid grasp of LLMs and embeddings: context management, tool calling, streaming, and latency/cost trade-offs. Monitoring and traceability mindset: OpenTelemetry, Langfuse/LangSmith. Strong software engineering fundamentals: testing, code reviews, error handling, reliability/resilience. Excellent problem-solving and communication skills; fluent in English (written & spoken). Preferred: Hands-on with agent frameworks (e.g. LangChain, LangGraph, PydanticAI) as well as FastAPI and FastMCP for MCP server development. Preferred: RAG and vector search proficiency (pgvector, OpenSearch) Preferred: Experience with relational databases (e.g., PostgreSQL); Databricks experience a plus. - Flexible benefits supporting leisure, and well‑being/sports programs - Life, accident, and disability insurance through group coverage - Employer‑supported pension plans with regular company contributions - Home office allowance to support hybrid or remote work - Extra Paid Holidays Benefits may vary depending on country, role, and employment conditions. | ---|--- YOUR APPLICATION| | We are committed to treating all applicants fairly and avoiding discrimination. We know how important work-life balance is, so our employees can work from home, from the office or combine both work environments. The possibilities of using the hybrid model are each time discussed with the manager. | ---|--- | |