Staff Software Engineer, AI-Native Systems

Accountabilities

• • Own the technical direction for a significant AI-native domain, such as agent architecture, platform abstractions, or evaluation and guardrail infrastructure.
  • Serve as technical lead for a squad or cross-team initiative by decomposing ambiguous problems, sequencing delivery, removing blockers, and keeping teams focused on measurable outcomes.
  • Lead architecture and design decisions, write and review design documentation, and establish clear technical ownership across complex initiatives.
  • Design and build production AI agents incorporating retrieval, orchestration, policy-based routing, tool/function calling, evaluation frameworks, and lifecycle observability.
  • Define standards for production-ready AI agents, including testability, rollback safety, cost controls, failure-mode management, and appropriate human-in-the-loop boundaries.
  • Build and extend shared AI platform abstractions, libraries, engineering patterns, and guardrails that enable teams to integrate AI capabilities safely and consistently.
  • Translate privacy, security, and regulatory requirements for sensitive data into practical technical architectures and engineering controls.
  • Deliver full-stack systems using TypeScript/Node.js and Python, including services, APIs, data-processing workflows, and internal interfaces.
  • Apply cloud-native infrastructure, event-driven architecture, CI/CD, monitoring, and observability practices to create scalable and reliable systems.
  • Own production deployment, monitoring, troubleshooting, and on-call responsibilities while continuously improving the operational health of inherited systems.
  • Partner with product, operations, clinical operations, and business leaders to identify valuable AI use cases, challenge low-value initiatives, and influence roadmap priorities.
  • Lead design sessions, proofs of concept, and collaborative build sessions to drive adoption and establish trust with internal users.
  • Define evaluation strategies and metrics covering agent accuracy, latency, safety, reliability, and cost-effectiveness.
  • Instrument AI systems so their behavior can be understood and evaluated beyond demonstrations, using data and feedback to continuously improve performance.
  • Mentor engineers through code reviews, design reviews, pairing, and direct feedback while creating reusable documentation, patterns, and best practices.
  • Build and strengthen the internal engineering community around AI-native and agentic development.
  • Within the first 90 days, develop a clear understanding of the AI platform, ship a meaningful contribution, and identify areas of high technical leverage.
  • Within six months, take ownership of a domain, lead technical direction within it, and establish a robust evaluation approach for deployed agents.
  • Within the first year, drive adoption of reusable patterns across teams and become a recognized technical multiplier for the broader engineering organization.

  Requirements

  • 8+ years of experience building and operating production software, with significant full-stack depth across TypeScript/Node.js and another programming language, preferably Python.
  • Proven technical leadership as an individual contributor, including domain ownership, leading multi-engineer initiatives, and influencing decisions across team boundaries without relying on formal authority.
  • Hands-on experience designing, deploying, and operating agentic systems in production, including retrieval, orchestration, tool/function calling, and evaluation.
  • Strong understanding of the practical strengths and limitations of LLMs and AI agents, with the judgment to determine where they provide genuine business value.
  • Demonstrated ability to take loosely defined problems from initial discovery through implementation, deployment, measurement, and iteration.
  • Experience using AI-powered development tools to accelerate engineering work, with sound judgment about when to trust, validate, or override AI-generated output.
  • Strong cloud-native engineering fundamentals, including CI/CD, observability, production operations, and system reliability.
  • Fluency with relational databases and SQL.
  • Strong written and verbal communication skills, including the ability to produce compelling technical design documents and communicate complex trade-offs to technical and executive audiences.
  • Comfort working remotely across functions and teams, with strong collaboration and stakeholder-management capabilities.
  • A high degree of autonomy, comfort with ambiguity, and a bias toward shipping measurable results.
  • Experience with production-scale agent frameworks or multi-agent architectures is strongly desired.
  • Background in model evaluation, guardrails, regression detection, and AI safety infrastructure is a plus.
  • Experience building platform capabilities used by multiple engineering teams is highly desirable.
  • Experience with workflow automation, forecasting-oriented products, or supply-and-demand matching systems is beneficial.
  • Experience working in a regulated environment such as healthcare/HIPAA or financial services, particularly involving sensitive data and AI, is strongly preferred.
  • Prior mentoring or formal technical-lead experience is advantageous.

  Benefits

  • Salary range: $185,725–$264,500 USD annually.
  • Remote-first work model for US-based employees.
  • Medical, dental, and vision coverage.
  • Life insurance and short- and long-term disability coverage.
  • 401(k) plan with company matching.
  • Flexible paid time off.
  • Paid parental leave.
  • Stock options.
  • Additional employee programs and perks supporting financial security, health, and well-being.
  • Opportunity to work in an AI-forward engineering environment where AI is integrated into both development practices and products.
  • Significant technical ownership and the opportunity to influence architecture, engineering standards, and organization-wide practices.
  • Inclusive workplace committed to equal employment opportunity and diverse perspectives.