Senior Python AI Engineer – LLM, Multi-Agent Systems

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

📋 Description

• Design and execute intricate agent orchestration logic utilizing LangGraph.

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

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

• Minimize end-to-end latency through the use of asynchronous processing and streaming (SSE).

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

• Optimize token utilization while maintaining answer quality.

• Develop automated evaluation pipelines with LangSmith.

• Initiate regression testing for prompts and agents to assess correctness and reliability before deployment.

• Refine advanced RAG retrieval techniques.

• Implement a hybrid approach to keyword and vector search, re-ranking, and query expansion.

• Create Ask Seeking Alpha, a high-load financial analysis system leveraging Large Language Models.

⛳️ Requirements

• Strong expertise in modern Python.

• In-depth knowledge of asynchronous programming patterns (asyncio).

• Experience with FastAPI and Pydantic v2.

• Practical experience with LangChain.

• Hands-on experience or a thorough conceptual understanding of LangGraph or comparable state-machine-based agent frameworks.

• Strategies for managing LLM hallucinations and ensuring consistent outputs.

• Experience in enforcing LLM compliance 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 between model size, latency, and cost.

• Familiarity with Elasticsearch, DSL queries, and analyzers.

• Knowledge of vector databases and embedding models.

• Background in FinTech or an understanding of financial data structures.

🏝️ Benefits

• Options for remote work.

• Continuous learning and career advancement opportunities.

• Flexible and balanced work environment.

• Benefits supporting personal well-being and professional aspirations.