Senior Python AI Engineer, LLM – Multi-Agent Systems

🔥 0 minutes ago

🇵🇱 Poland – Remote

⏰ Full Time

🟠 Senior

🗣️ LLM Engineer

👻 Ghost score 15%

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Seeking Alpha

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📣 Marketing

💸 Finance

💰 $7M Series B on 2009-12

Consulting • Marketing • Finance

Seeking Alpha is the world’s largest investing community, powered by the wisdom and diversity of crowdsourcing. It connects millions of investors to discover and share investment ideas, discuss breaking news, and make informed investment decisions. The platform features a wide range of investment research, including stocks, ETFs, commodities, and cryptocurrency, with contributions from over 7,000 authors publishing thousands of investing ideas monthly. Seeking Alpha also offers exclusive tools and subscription plans to enhance investing strategies and provide real-time insights to individual investors.

📋 Description

• Design and implement complex agent orchestration logic using LangGraph • Define state management, conditional routing, and error handling within the agent graph • Build and optimize the tool layer using function calling for interactions with internal financial APIs and databases • Reduce end-to-end latency through asynchronous processing and streaming (SSE) • Implement semantic caching strategies to minimize API costs and response time • Optimize token usage while maintaining answer quality • Implement automated evaluation pipelines using LangSmith • Set up regression testing for prompts and agents to measure correctness and faithfulness before deployment • Refine retrieval strategies using hybrid keyword and vector search, re-ranking, and query expansion

🎯 Requirements

• Strong proficiency in modern Python • Deep understanding of asynchronous programming (asyncio) patterns • Experience with FastAPI and Pydantic (v2) • Production experience with LangChain • Hands-on experience or deep conceptual understanding of LangGraph or similar state-machine based agent frameworks • Strategies for handling LLM hallucinations and ensuring reliable outputs, including self-correction loops and prompting techniques such as CoT/ReAct • Experience forcing LLMs to adhere to strict schemas using Pydantic/JSON mode • Advanced context-window management strategies, including summarization chains, sliding windows, and selective context injection • Understanding trade-offs between model size, latency, and cost • Experience with Elasticsearch, DSL queries, and analyzers (nice to have) • Knowledge of vector databases and embedding models (nice to have) • Background in FinTech or familiarity with financial data structures (nice to have)

🏖️ Benefits

• Flexible, balanced environment with remote work options • Ongoing learning and career advancement opportunities • Workplace perks supporting personal well-being and professional goals