answersnow - Staff Engineer AI/ML
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Requirements
• 8+ years of professional software engineering experience, with at least 3 years in a senior or staff-level role • Deep expertise in JavaScript and TypeScript in a production full-stack environment • Strong command of React, Node.js/Express, and Postgres — you can reason about performance, reliability, and maintainability at each layer • Proven experience designing and owning distributed systems or data pipeline architectures on AWS (ECS, RDS, S3, Lambda experience valued) • Track record of technical mentorship — you've made engineers around you measurably better • Excellent written and verbal communication; you can write an architecture doc, run a design review, and brief a non-technical executive in the same day • Experience working in or leading engineering at a growth-stage startup — you understand the balance between velocity and sustainability • Familiarity with ETL pipelines, AI/LLM integration patterns, or data-intensive systems is a strong plus • Significant experience architecting and deploying production-grade ML/AI systems, including LLM integration and model lifecycle management. • Experience with healthcare or regulated data environments (HIPAA compliance, PHI handling) • Familiarity with event-driven architectures, message queues, or streaming pipelines • Prior experience as an engineering manager who returned to an IC track (player-coach background welcome) • Contributions to open source or engineering blog posts / conference talks
Responsibilities
• Technical Leadership • Own and evolve the architecture of our core platform: React frontend, Node.js/Express APIs, Postgres, and AWS ECS infrastructure • Drive our JavaScript → TypeScript migration, establishing patterns, tooling, and standards the team can follow • Design and extend our ETL pipeline and config-driven AI integration framework, enabling engineers to ship AI-powered features faster and more reliably • Lead technical design reviews, create architecture decision records (ADRs), and ensure engineering decisions are documented and defensible • Identify and resolve systemic technical debt — not just flagging it, but owning the plan to address it • Define and execute the technical strategy for integrating ML/AI models into our core platform, ensuring scalability, performance, and reliability. • Engineering Culture & Mentorship • Mentor engineers across all levels — pair, review, coach, and grow the team's collective capability • Establish and maintain engineering standards: code quality, testing practices, observability, on-call runbooks, and incident response • Serve as a technical resource and thought partner for product, clinical, and business stakeholders • Help define the engineering hiring bar and participate in the interview process • Delivery & Operations • Partner with engineering leadership and product to scope, sequence, and de-risk large technical initiatives • Lead by example on production support — define runbooks, own post-mortems, and drive systemic fixes from incidents • Work across UI, API, DB, and infrastructure layers with genuine depth in at least two
Benefits
• We're looking for a Senior Engineering Manager who knows that great engineering leadership is about growing people, removing obstacles, and making the team better — not writing the most code. You've led teams before. You know how to hold a high bar for craft while keeping engineers energized and growing. You understand that a team of four highly effective engineers with strong habits will outperform a team of twelve with unclear expectations. • You'll manage a team of Engineering Team Leads, each of whom runs a squad of full-stack engineers. You own the health of the engineering organization: hiring, performance, culture, delivery, and the processes that keep everything running. You partner closely with the CTO, product leadership, and clinical stakeholders to ensure engineering is building the right things, the right way. • This is a player-coach role in spirit — you should be technically credible and able to engage meaningfully in architecture discussions — but your primary output is team output, not individual code. • Fully remote – work from anywhere in the U.S. • Flexible hours with an async-friendly team culture
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