COMPANY OVERVIEW

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

About the Role
We're looking for a hands-on engineer to build AI-powered tooling and automation for our operations, trading support, and technology teams. You'll design and ship production scripts, pipelines, and lightweight applications that connect LLMs (Claude, GPT, and similar) to internal data and systems, replacing manual processes with reliable automated workflows. This is a build-first role for someone who thinks like a software engineer, not a business analyst who occasionally scripts.

What You'll Do

• Design, build, and maintain production-grade automations, scripts, and services (Python, SQL, APIs) that integrate LLMs with internal data sources and systems
• Architect data pipelines that extract, clean, validate, and route data supporting AI-driven workflows
• Build and iterate on prompt-engineering systems, evaluation harnesses, and testing frameworks to measure and improve output quality and reliability
• Prototype new AI-assisted tools end to end: design, build, test, deploy, monitor
• Own uptime and reliability of deployed AI tools; debug failures, write monitoring/alerting, and fix root causes
• Integrate with internal systems and third-party APIs to automate workflows across the trade lifecycle, reconciliations, settlements, confirmations, corporate actions, and reporting
• Write clean, maintainable, version-controlled code with appropriate documentation and testing
• Evaluate new models, frameworks, and vendor tools for fit and integrate the ones that add value
• Partner with operations and business stakeholders to translate requirements into technical specs, but own the technical execution independently

What We're Looking For

• 1-5 years of software engineering, data engineering, or applied AI/ML experience
• Strong proficiency in Python (production code, not just scripts) and SQL
• Demonstrated experience building with LLM APIs: prompt engineering, RAG, agentic workflows, evals, or fine-tuning
• Comfort with the full engineering lifecycle: version control, testing, deployment, monitoring
• Experience with APIs, automation frameworks, or data pipeline tools
• Ability to work independently from a rough business requirement to a shipped, reliable tool
• Bachelor's degree in Computer Science, Engineering, or a related quantitative field

Nice to Have

• Experience in financial services, hedge funds, or capital markets (not required — we'll teach the domain)
• Experience with agent frameworks, vector databases, or LLM orchestration tools (LangChain, LlamaIndex, etc.)
• Familiarity with cloud infrastructure (AWS/Azure) and CI/CD