Staff AI Execution Engineer
New
Based in the United StatesFull-TimeStaff
Salary200,000 - 220,000 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- GraphQLPythonSQLSnowflakedbtLangChainDistributed Systems
Requirements
- 8+ years of software engineering experience, with deep expertise in building production-scale systems.
- Proven experience designing and shipping AI or machine learning systems into production environments.
- Strong hands-on experience with agentic AI workflows, including orchestration, memory systems, and evaluation design.
- Expertise with modern AI tooling and frameworks such as LangChain, LangGraph, GraphQL, and MCP.
- Fluency in AI-native development environments and tools (e.g., Cursor, Claude Code, Devin or similar).
- Strong understanding of evaluation methodologies for AI systems and performance measurement at scale.
- Advanced proficiency in data engineering and analysis using SQL and Python, with experience in platforms like Snowflake and dbt.
- Familiarity with distributed data and event-driven systems (e.g., Kafka, CDC pipelines, APIs) is highly desirable.
- Strong technical leadership, communication skills, and a track record of mentoring engineers and driving technical direction.
Responsibilities
- Design, build, and deploy production-grade agentic AI systems that power advisor-facing financial intelligence products.
- Own end-to-end delivery of AI features, including agent orchestration, memory systems, evaluation frameworks, and production hardening.
- Architect scalable AI workflows that ensure reliability, observability, and performance across distributed systems.
- Develop and implement evaluation frameworks to measure, improve, and optimize agent behavior at scale.
- Leverage agentic AI tools and frameworks to accelerate development velocity and improve engineering productivity.
- Drive best practices for AI-native engineering, including prompt design, multi-agent orchestration, and context optimization.
- Collaborate with data and product teams to translate complex financial datasets into meaningful AI-driven insights.
- Mentor engineers and contribute to raising the technical bar across AI system design and delivery.
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