Staff Software Engineer

Assured•New York, NY

17d•$300,000 - $350,000•Onsite

About The Position

We’re looking for a Staff Software Engineer to help architect, build, and productize our AI/ML infrastructure. You'll be the bridge between research, product, customers, and engineering, driving AI adoption from strategy through production at scale. This role is ideal for someone who thrives in early-stage environments, enjoys owning things end to end, and wants their work to have a measurable impact on an industry that desperately needs modern infrastructure.

Requirements

10+ years experience building and scaling complex, distributed systems or workflow-heavy SaaS platforms.
Deep experience implementing AI harnesses.
Recent experience in startups.
Proven ability to own architecture and make high-stakes technical decisions in ambiguous, high-growth environments.
Deep understanding of modern cloud architecture and full software stacks.
Excellent communication — able to clearly explain technical trade-offs to technical and non-technical audiences alike.

Nice To Haves

Want to lead AI projects from idea to deployment.
Want to own architecture, projects, and culture.
Thrive in a 0→1 environment, building from scratch and scaling from concept to production.
Care deeply about impact — accelerating patient access by fixing the infrastructure of healthcare.
Believe great products emerge from tight collaboration between product, engineering, and operations.
Want your work to outlast you — building systems that become part of healthcare’s invisible infrastructure.

Responsibilities

Design and evolve a modular architecture to power configurable healthcare workflows at scale.
Build a workflow orchestration engine capable of handling thousands of concurrent stateful tasks (credentialing, verification, enrollment).
Define and optimize integration frameworks to connect with thousands of external systems — web portals, APIs, PDFs, spreadsheets.
Drive reliability, auditability, and performance through observability, self-healing, and clear fault-domain boundaries.
Lead the design and deployment of AI-powered digital workers — LLM- and rules-driven agents that perform operational workflows end-to-end.
Evaluate AI tools, frameworks, and third-party APIs, ensuring alignment with platform goals and data protection requirements.
Partner with product, engineering, and analytics to discover use cases, build features, and deliver value.
Engage with customers to understand operational challenges, validate assumptions, and iterate solutions quickly.
Provide technical mentorship to the engineering team.