Staff Software Engineer, AI-Native Systems

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, AI-Native Systems based in United States.

This is a staff-level technical leadership role focused on building production-grade, AI-native systems in a regulated healthcare environment.

You’ll define architecture and technical direction for agentic platforms, AI workflows, and shared engineering foundations.

The role combines hands-on software development with cross-team leadership, allowing you to shape both technology and engineering practices.

You’ll work across TypeScript/Node.js, Python, cloud infrastructure, APIs, data systems, and event-driven architectures.

A major focus will be creating reliable, measurable, secure, and cost-effective AI agents capable of carrying meaningful operational workloads.

You’ll partner closely with product, clinical operations, business, and engineering leaders to identify high-value opportunities and guide delivery.

This remote-first opportunity is ideal for an experienced engineer who thrives on ambiguity, technical ownership, and measurable outcomes.

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.