Staff Software Engineer, AI Developer Productivity
New
J
JobgetherFinancial technology
Based in the United StatesFull-TimeStaff
SalaryAnnual base salary ranging from $218,025 to $256,500
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Job Details
- 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.
- Required Skills
- PythonJavaGoLangChain
Requirements
- At least 8 years of software engineering experience.
- At least 2 years developing AI- or LLM-powered developer tools, agentic workflows, or automated code engineering systems.
- Experience designing, building, and deploying production-grade systems that integrate LLMs or AI agents into software development lifecycles.
- Experience with code generation, automated code review, and CI/CD automation.
- Strong proficiency in Java, Python, Go, or comparable backend programming languages.
- Hands-on experience developing and orchestrating AI agent architectures with LangChain, LangGraph, or custom-built solutions.
- Strong understanding of backend architecture, software development processes, automation, testing, and deployment practices.
- Experience building tools and workflows that improve engineering efficiency, software quality, and developer experience.
- Familiarity with financial systems, high-reliability engineering, or regulated industries where security, correctness, compliance, and auditability are essential.
- Ability to use generative AI responsibly, maintain human oversight, and deliver reliable, business-ready solutions.
- Technical communication, architectural decision-making, and ability to influence engineering standards and adoption across teams.
Responsibilities
- Lead the architecture, development, and deployment of agentic AI solutions for automated refactoring, test generation, and proactive bug detection.
- Integrate large language models and AI agents into code review, development, testing, and deployment workflows.
- Create reliable, production-ready systems that automate repetitive engineering tasks.
- Partner with platform AI, developer experience, infrastructure, and product engineering teams on shared technologies and institutional requirements.
- Promote implementation, adoption, and continuous improvement of AI-assisted development practices.
- Establish and monitor indicators for development velocity, code quality, workflow efficiency, cost optimization, and developer satisfaction.
- Define technical guidelines for secure, reliable, and governed human-AI collaboration.
- Maintain human oversight, auditability, and security controls for AI agents in sensitive financial systems.
- Identify opportunities to expand AI-driven engineering capabilities and influence the developer productivity strategy.
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