Staff Software Engineer, AI Developer Productivity

Accountabilities:: 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. 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. Develop scalable AI capabilities: Create reliable, production-ready systems that automate repetitive engineering tasks and improve software development efficiency. 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. Drive AI adoption: Promote AI-assisted development practices across engineering teams, supporting implementation, adoption, and continuous improvement. Measure engineering impact: Establish and monitor performance indicators related to development velocity, code quality, workflow efficiency, cost optimization, and developer satisfaction. Establish technical standards: Define best practices and technical guidelines for human-AI collaboration, ensuring AI-powered development remains secure, reliable, and appropriately governed. Ensure responsible AI implementation: Maintain appropriate human oversight, auditability, and security controls when deploying AI agents in sensitive financial systems. Shape the technical roadmap: Identify opportunities to expand AI-driven engineering capabilities and influence the long-term developer productivity strategy. Requirements: 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. 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. Programming expertise: Strong proficiency in Java, Python, Go, or comparable backend programming languages. AI agent frameworks: Hands-on experience developing and orchestrating AI agent architectures using frameworks such as LangChain, LangGraph, or custom-built solutions. Software engineering fundamentals: Strong understanding of backend architecture, software development processes, automation, testing, and deployment practices. Cross-functional collaboration: Proven ability to work effectively with platform, infrastructure, and product teams to deliver tools and solutions adopted by large engineering organizations. Developer productivity expertise: Experience building tools and workflows that improve engineering efficiency, software quality, and developer experience. Financial or regulated environments: Familiarity with financial systems, high-reliability engineering, or regulated industries where security, correctness, compliance, and auditability are essential. Responsible AI practices: Ability to use generative AI responsibly, maintain human oversight, and deliver reliable, business-ready solutions that generate measurable improvements in efficiency, cost, and quality. Communication and leadership: Strong technical communication, architectural decision-making, and the ability to influence engineering standards and drive adoption across multiple teams. Adaptability: Comfortable working in a demanding, fast-moving environment with complex technical challenges and evolving priorities. Benefits: Competitive compensation: Annual base salary ranging from $218,025 to $256,500 , depending on geographic location and other relevant factors. Additional compensation: Potential eligibility for equity awards and performance-based bonuses. Healthcare coverage: Medical, dental, and vision insurance with generous employer contributions. Health savings account: Employer contributions to a Health Savings Account (HSA) with each pay period. Insurance protection: Life and disability insurance coverage. Retirement planning: Access to a company-sponsored 401(k) retirement savings plan. Wellness support: Wellness allowance to support personal health and well-being. Remote flexibility: Remote-first working environment, with quarterly in-person team gatherings known as working sessions or "surges." Connectivity allowance: Mobile phone and internet reimbursement. Paid time off: Competitive vacation and leave policies. Community involvement: Paid volunteer time to support charitable and community initiatives. Family-building support: Fertility treatment consultations and financial benefits. Flexible compensation options: Possibility of receiving eligible compensation in digital currency. Professional development: Opportunity to work with advanced AI technologies, shape engineering practices, and influence the future of AI-assisted software development.