AI/ML Lead Engineer

Location: Hybrid, working from the Stamford, San Ramon, or San Mateo offices 3 days per week; applicants must be authorized to work for any employer in the United States.

Salary: $180,000–$212,000 annually, plus a discretionary bonus.

Company

hirify.global is a global asset manager, with O’Shaughnessy Asset Management providing custom indexing and portfolio management services through its Canvas platform.

What you will do

• Design and implement production-grade multi-agent systems and agent workflows for financial advisors.
• Build retrieval, reasoning, tool execution, validation, compliance, memory, and state-management capabilities.
• Develop distributed agent-execution services with observability, monitoring, fault tolerance, and strong failure handling.
• Embed AI agents and chatbots into client-facing platforms to generate portfolio and book-of-business insights.
• Create evaluation frameworks for reasoning accuracy, groundedness, hallucination mitigation, financial correctness, and compliance.
• Partner with product, design, and engineering teams while optimizing model serving, vector databases, caching, orchestration, latency, cost, and reliability.

Requirements

• 5+ years of software engineering experience, including 2+ years building and deploying LLM, GenAI, or agent-based systems in production.
• Experience with multi-step agent workflows using LangChain, OpenAI function or tool calling, or similar frameworks.
• Expert-level Python proficiency and experience building distributed services or microservice architectures.
• Hands-on experience with vector databases, RAG architectures, and data-grounding techniques.
• Experience implementing observability, monitoring, and fault-tolerant systems for high-availability applications.
• U.S. work authorization is required; visa sponsorship or transfer of employment visa sponsorship is not available.

Nice to have

• Experience in asset management, wealth management, or portfolio analytics.
• Experience with LLM evaluation, model governance, hallucination mitigation, groundedness, accuracy testing, or compliance monitoring.
• Experience with multi-agent architectures, model serving, Docker, Kubernetes, AWS, Azure, or GCP.
• Master’s or PhD in Computer Science, Machine Learning, AI, or a related field.

Culture & Benefits

• Hybrid work with regular office presence.
• Annual discretionary bonus and 401(k) plan with a generous match.
• Healthcare, insurance, disability benefits, employee stock investment opportunities, and paid time off.
• Learning resources, career development programs, education expense reimbursement, and a wellbeing program.