Senior Python AI Engineer, LLM – Multi-Agent Systems

This is a fully remote position, open to applicants in Poland.

📋 Description

• Create and execute intricate agent orchestration logic utilizing LangGraph.

• Establish state management, conditional routing, and error handling within the agent graph.

• Develop and enhance the tool layer by employing function calling for interactions with internal financial APIs and databases.

• Decrease end-to-end latency through asynchronous processing and streaming (SSE).

• Apply semantic caching strategies to reduce API costs and improve response times.

• Optimize token utilization while ensuring quality of answers.

• Create automated evaluation pipelines using LangSmith.

• Implement regression testing for prompts and agents to assess correctness and fidelity prior to deployment.

• Enhance retrieval strategies by utilizing hybrid keyword and vector search, re-ranking, and query expansion.

⛳️ Requirements

• Strong expertise in modern Python.

• Profound knowledge of asynchronous programming (asyncio) patterns.

• Experience with FastAPI and Pydantic (v2).

• Production experience with LangChain.

• Practical experience or a deep conceptual grasp of LangGraph or similar state-machine-based agent frameworks.

• Strategies for managing LLM hallucinations and ensuring dependable outputs, including self-correction loops and prompting techniques such as CoT/ReAct.

• Experience in enforcing LLMs to comply with strict schemas using Pydantic/JSON mode.

• Advanced strategies for context-window management, including summarization chains, sliding windows, and selective context injection.

• Understanding the trade-offs among model size, latency, and cost.

• Familiarity with Elasticsearch, DSL queries, and analyzers (preferred).

• Knowledge of vector databases and embedding models (preferred).

• Background in FinTech or familiarity with financial data structures (preferred).

🏝️ Benefits

• Flexible and balanced environment with options for remote work.

• Continuous learning and career advancement opportunities.

• Workplace perks that support personal well-being and professional aspirations.