2 weeks ago

Senior Python AI Engineer (LLM & Multi-Agent Systems)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Build and scale “Ask Seeking Alpha,” a high-load financial analysis system powered by large language models. Design multi-agent orchestration with LangGraph, engineer tool/function-calling integrations with internal financial APIs and databases, and optimize performance via async processing, streaming, caching, and token efficiency. Ensure quality and reliability with LangSmith evaluations and robust handling of non-deterministic LLM behavior, including advanced hybrid RAG with re-ranking and query expansion.

Location: Israel

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and implement complex agent orchestration logic using LangGraph, including state management, conditional routing, and error handling.
•Build and optimize the tool/function-calling layer that lets LLMs interact accurately with internal financial APIs and databases.
•Reduce end-to-end latency using asynchronous processing and streaming (SSE), and optimize token usage and semantic caching to control cost.
•Implement observability and evaluation pipelines with LangSmith, including regression testing for prompts and agents to measure quality before deployment.
•Improve retrieval for advanced RAG using hybrid search (keyword + vector), re-ranking, and query expansion.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Strong modern Python experience with mandatory async (asyncio) patterns, plus FastAPI and Pydantic (v2).
•Production experience with LangChain and hands-on or deep conceptual understanding of LangGraph (or similar state-machine agent frameworks).
•Manage LLM non-determinism with techniques like self-correction loops and prompting approaches such as CoT/ReAct.
•Produce structured outputs by enforcing strict schemas (Pydantic/JSON mode) for reliable downstream processing.
•Optimize context and inference economics using strategies like summarization/sliding windows and smart model routing.

Experience:FinTech

Tech Stack:PythonAsyncioFastAPILangChainLangGraphPydanticElasticsearchAWS BedrockOpenAI APILangSmithSSE

Company Brief

Seeking Alpha

Provides financial news, market analysis, and investment research for retail investors and professionals. The platform features articles, earnings coverage, stock ideas, portfolio tools, and community discussions focused on public markets.

Industry: News, Journalism & Broadcasting

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: New York City, United States

Founded: 2004

Website LinkedIn

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Seeking Alpha

2 weeks ago

Senior Python AI Engineer (LLM & Multi-Agent Systems)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: Israel

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and implement complex agent orchestration logic using LangGraph, including state management, conditional routing, and error handling.
•Build and optimize the tool/function-calling layer that lets LLMs interact accurately with internal financial APIs and databases.
•Reduce end-to-end latency using asynchronous processing and streaming (SSE), and optimize token usage and semantic caching to control cost.
•Implement observability and evaluation pipelines with LangSmith, including regression testing for prompts and agents to measure quality before deployment.
•Improve retrieval for advanced RAG using hybrid search (keyword + vector), re-ranking, and query expansion.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Strong modern Python experience with mandatory async (asyncio) patterns, plus FastAPI and Pydantic (v2).
•Production experience with LangChain and hands-on or deep conceptual understanding of LangGraph (or similar state-machine agent frameworks).
•Manage LLM non-determinism with techniques like self-correction loops and prompting approaches such as CoT/ReAct.
•Produce structured outputs by enforcing strict schemas (Pydantic/JSON mode) for reliable downstream processing.
•Optimize context and inference economics using strategies like summarization/sliding windows and smart model routing.

Experience:FinTech

Tech Stack:PythonAsyncioFastAPILangChainLangGraphPydanticElasticsearchAWS BedrockOpenAI APILangSmithSSE

Company Brief

Seeking Alpha

Industry: News, Journalism & Broadcasting

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Headquarters: New York City, United States

Founded: 2004

Website LinkedIn