Staff Software Engineer, AI Developer Productivity
United States1h ago
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Key details
- Location
- United States
- Work style
- Remote
- Level
- Senior
- Job type
- Full-time
- Experience
- 8–11 yrs
- Function
- Software engineering
- Focus area
- AI / ML
- Posted
- 1h ago
Skills
About the role
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Software Engineer, AI Developer Productivity based in the United States.
In this role, you will help transform software engineering practices by designing and deploying advanced AI-powered tools and agentic workflows. As a founding engineering team member, you will shape how developers build, review, test, and deliver software across critical financial technology systems. You will lead the architecture and implementation of intelligent automation solutions that improve code quality, accelerate development cycles, and increase engineering productivity. Working closely with AI, platform, infrastructure, and product teams, you will develop scalable capabilities tailored to demanding institutional environments. You will also establish best practices for responsible AI adoption, ensuring security, reliability, and human oversight remain central to development. This is an opportunity to make a significant technical impact in a fast-paced, remote-first environment at the intersection of artificial intelligence and financial infrastructure.
Accountabilities:
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Design AI-powered engineering workflows: Lead the architecture, development, and deployment of agentic AI solutions that continuously improve code quality through automated refactoring, test generation, and proactive bug detection.
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Build developer productivity tools: Integrate large language models (LLMs) and AI agents into engineering workflows, supporting activities ranging from code review and development to testing and deployment.
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Develop scalable AI capabilities: Create reliable, production-ready systems that automate repetitive engineering tasks and improve software development efficiency.
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Collaborate across technical teams: Partner with platform AI, developer experience (DevX), infrastructure, and product engineering teams to leverage shared technologies while addressing specific institutional requirements.
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Drive AI adoption: Promote AI-assisted development practices across engineering teams, supporting implementation, adoption, and continuous improvement.
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Measure engineering impact: Establish and monitor performance indicators related to development velocity, code quality, workflow efficiency, cost optimization, and developer satisfaction.
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Establish technical standards: Define best practices and technical guidelines for human-AI collaboration, ensuring AI-powered development remains secure, reliable, and appropriately governed.
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Ensure responsible AI implementation: Maintain appropriate human oversight, auditability, and security controls when deploying AI agents in sensitive financial systems.
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Shape the technical roadmap: Identify opportunities to expand AI-driven engineering capabilities and influence the long-term developer productivity strategy.
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Professional experience: At least 8 years of software engineering experience, including a minimum of 2 years developing AI- or LLM-powered developer tools, agentic workflows, or automated code engineering systems.
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Production AI experience: Demonstrated success designing, building, and deploying production-grade systems that integrate LLMs or AI agents into software development lifecycles, including code generation, automated code review, and CI/CD automation.
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Programming expertise: Strong proficiency in Java, Python, Go, or comparable backend programming languages.
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AI agent frameworks: Hands-on experience developing and orchestrating AI agent architectures using frameworks such as LangChain, LangGraph, or custom-built solutions.
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Software engineering fundamentals: Strong understanding of backend architecture, software development processes, automation, testing, and deployment practices.
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Cross-functional collaboration: Proven ability to work effectively <