Founding GenAI Engineer (Front Office Investing)

Verition Fund Management LLC; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

A multi-strategy hedge fund is seeking a GenAI Engineer to develop a cutting-edge research infrastructure that influences real-time investment decisions. This role involves working directly with portfolio managers and implementing solutions that leverage large language models, providing a unique opportunity to design from the ground up without legacy constraints. Ideal candidates will possess strong Python skills and a solid background in AI development.

Qualifications

• Experience building and shipping working code.
• Familiarity with multimodal APIs and vector databases.
• Interest in equities or macro is a plus.

Responsibilities

• Design and build GenAI-native research infrastructure.
• Use LLM's for text and audio analysis with microservices.
• Collaborate with various teams for compliance and security.

Skills

Fluency in Python

Strong communication

Experience with vector DBs

Familiarity with LangChain/LlamaIndex

Education

0–5 years of industry experience or strong grad/post-doc research background

Tools

AWS DevOps

Docker

Python

Job description

Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.

We are looking for a talented GenAI Engineer to build out a GenAI-native research infrastructure from scratch that powers real-time investment decisions. You'll partner directly with a Portfolio Manager who codes and works daily in the LLM space—taking ideas from research papers to prototype to production within AWS. This role is embedded on the trading team so you can build solutions that directly influence portfolio positions. This is a greenfield project that the right candidate gets to design and build from scratch, zero legacy code.

Responsibilities:

• Use LLM’s to ingest unstructured text and audio, design chunking and embedding strategies, and serve results through RAG/hybrid-search microservices.
• Build regression tests and A/B frameworks; track drift, latency, and analyst-acceptance metrics.
• Ship weekly, log everything, and refine based on tight front-office feedback loops.
• Test SOTA papers, run ablations, and containerize winners via Docker on AWS GPU infrastructure (EKS/Batch).
• Work with DevOps, Data, and Risk teams to meet compliance and security standards.

Qualifications:

• 0–5 years of industry experience or strong grad/post-doc research background.
• Evidence of building and shipping working code (not just decks or papers).
• Fluency in Python (asyncio, typing, PyTest); familiarity with LangChain/LlamaIndex or similar tools.
• Experience with vector DBs (Weaviate, Qdrant, PGVector) and multimodal APIs.
• Strong communicator comfortable working directly with investment pros.
• Location: Ideally San Francisco, but open to this person working remotely
• Nice to Have:
• OSS or publication record in NLP, speech diarization, or information retrieval.
• Experience with AWS DevOps (Helm, EKS/Fargate, CDK/Terraform, Batch).
• Interest in equities or macro (finance knowledge not required).

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