Member of Technical Staff | Agentic AI
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Before you apply
SalaryNo pay range posted
LocationMenlo Park
Work modehybrid
Typefull-time
SeniorityLead
DepartmentEngineering
Company size11–50 people
PostedOct 13, 2026 · 3w ago
Verified live21h ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science or related field
Master's degree in Computer Science or related field
PhD in Computer Science or related field
Equivalent practical experience
Built agent systems at a frontier AI lab, agentic startup, top fund, big tech company, or similar
Deployed agents in production
Experience with orchestration, tool use, context management and grounding
Understanding of agent failure modes
Built evaluations and observability to diagnose and improve agents
Understanding of financial markets and strong interest in investing
Experience with unstructured financial data (Bloomberg, Capital IQ, Refinitiv)
Experience with agent safety, sandboxing or guardrails in high-stakes environments
Current legal authorization to work in the US required
Benefits
Health insurance
Dental insurance
Vision insurance
Commuter benefits
Relocation assistance
About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We’re building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
At Poesis, we are pioneering AI for investing, opening the door to improved alpha discovery, higher quality decision-making and intelligent risk management. AI agents are a core part of how we make this a reality and we’re looking for an experienced software engineer to help lead our agentic efforts. The work sits at the intersection of frontier models and production engineering, exploring what new models and harnesses make possible and turning those capabilities into real systems. This is a unique opportunity to help define how frontier AI is used in investing and shape the technical direction of our agent platform from an early stage.
Challenges You’ll Work On
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Design and build the architecture behind a scalable, reliable agent platform that evolves as models advance
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Design and build agent-driven workflows and systems for complex investment problems.
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Develop evaluation, observability and feedback systems that make agents more reliable and capable over time.
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Solve the infrastructure and deployment challenges of running agents reliably in production.
About You
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You’ve built agent systems at a frontier AI lab, agentic startup, top fund, big tech company, or similar.
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You’ve deployed agents in production and know what it takes to make them reliable.
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You have experience with orchestration, tool use, context management and grounding.
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You understand agent failure modes and have built the evaluations and observability needed to diagnose and improve them.
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You understand financial markets and have a strong interest in investing.
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You have a BS/MS/PhD in Computer Science or a related field, or equivalent practical experience.
Nice to Have
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Experience working with unstructured financial data and data providers (Bloomberg, Capital IQ, Refinitiv).
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Experience with agent safety, sandboxing or guardrails in high-stakes environments.
Location
Hybrid, 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
Working at Poesis
As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.