We are looking for a senior staff-level engineer to design, build, and operate high-scale distributed systems and lead agentic-first development practices. This role works across product, infrastructure, data, security, and platform teams to turn ambiguous goals into durable architectures and production-quality systems. You will stay deeply hands-on while setting technical direction, mentoring engineers, and raising the engineering bar.
Internal Responsibilities
Lead the design, implementation, testing, and operation of high-scale distributed systems, APIs, services, data pipelines, and platform components.
Own major initiatives end to end, from ambiguous requirements and architecture through rollout, observability, and production support.
Architect for reliability, scalability, low latency, fault isolation, backpressure, graceful degradation, data consistency, and operational visibility.
Raise engineering quality through automated testing, code review, CI/CD, deployment automation, incident follow-up, and documentation.
Use agentic-first development practices to accelerate prototyping, debugging, refactoring, test generation, documentation, and delivery while maintaining human ownership.
Build or integrate AI/agent workflows, including tool use, RAG, agent harnesses, evaluations, workflow automation, AI observability, and LLM-backed experiences.
Apply secure-by-default and responsible-AI practices across identity, access control, secrets handling, dependency hygiene, data protection, threat modeling, and secure code review.
Partner with product, architecture, security, operations, and peer engineering teams to translate broad goals into technical plans and tradeoff decisions.
Mentor engineers, lead design reviews, and define standards for maintainable, supportable, production-grade software across teams.
Strong programming ability in one or more languages such as Java, Python, Go, C++, Rust, or TypeScript.
Proven experience designing and operating distributed systems, cloud services, SaaS platforms, data systems, or infrastructure services at scale.
Deep knowledge of system design, APIs, data modeling, concurrency, asynchronous processing, failure modes, performance analysis, and production troubleshooting.
Experience with cloud platforms, containers, CI/CD, observability, automated testing, deployment automation, and operational readiness.
Hands-on use of AI-assisted and agentic development tools such as ChatGPT, Claude, Copilot, Cursor, or similar tools.
Practical experience with LLM patterns such as prompt engineering, RAG, tool use, agent frameworks, harnesses, evaluations, or workflow automation.
Working security knowledge across identity, access control, secure coding, dependency management, data privacy, and incident-aware engineering.
Experience building high-scale, low-latency, high-availability, multi-tenant distributed systems and influencing architecture across teams.
Experience with agentic AI platforms, LLM evaluation, AI observability, guardrails, tool orchestration, or developer productivity tooling.
Experience in regulated, enterprise, healthcare, cloud infrastructure, data platform, or security-sensitive environments.
External Responsibilities
Lead the design, implementation, testing, and operation of high-scale distributed systems, APIs, services, data pipelines, and platform components.
Own major initiatives end to end, from ambiguous requirements and architecture through rollout, observability, and production support.
Architect for reliability, scalability, low latency, fault isolation, backpressure, graceful degradation, data consistency, and operational visibility.
Raise engineering quality through automated testing, code review, CI/CD, deployment automation, incident follow-up, and documentation.
Use agentic-first development practices to accelerate prototyping, debugging, refactoring, test generation, documentation, and delivery while maintaining human ownership.
Build or integrate AI/agent workflows, including tool use, RAG, agent harnesses, evaluations, workflow automation, AI observability, and LLM-backed experiences.
