Staff Software Development Engineer – Tech Lead

Emploi pas sur LinkedIn

🕒 il y a 8 jours

🍂 Massachusetts – Distant

🍂 Massachusetts – Remote

💵 $130 295 - $260 590 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

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CVS Health

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1963

🏥 Santé

⚕️ Assurance santé

🛒 Commerce de détail

Healthcare • Healthcare Insurance • Retail

CVS Health est une entreprise américaine de premier plan dans le domaine de la santé, dédiée à l'amélioration de l'accès et de l'accessibilité financière des soins de santé. L'entreprise s'appuie sur une approche globale qui comprend les services de santé, l'assurance santé et la gestion des prestations pharmaceutiques. À travers ses filiales, telles qu'Aetna et CVS Caremark, CVS Health propose une gamme de services qui favorisent le bien-être, la gestion des maladies chroniques et une couverture abordable des médicaments prescrits. CVS Health exploite des pharmacies de proximité, fournit des services de pharmacie par correspondance et gère des programmes de médicaments spécialisés, visant à rendre les soins de santé pratiques et accessibles à tous. Animée par une mission de connecter les individus aux services de soins essentiels, CVS Health s'engage à favoriser des communautés en meilleure santé et à soutenir le bien-être de toutes les personnes.

Description

• Architect, design and build full-stack AI application capabilities — spanning agent backend services, APIs, and front-end interfaces — that enable engineering teams to ship agentic features reliably. • Design and build full-stack AI application capabilities — spanning agent backend services, APIs, and front-end interfaces — that enable engineering teams to ship agentic features reliably. • Lead technical design for agent-powered product features using CopilotKit for in-app copilots and generative UI, and Deep Agents -style architectures (planning, sub-agent delegation, long-horizon task execution) for complex workflows. • Instrument, trace, and evaluate agent behavior in production using LangSmith , driving down latency, cost, and error rate through systematic evaluation rather than guesswork. • Own the connective tissue between backend agent logic and frontend experience — API design, state synchronization, and human-in-the-loop approval flows. • Review and influence designs produced across the team; set and enforce engineering standards for agent reliability, prompt/version management, and rollback strategies. • Mentor senior and mid-level engineers on agentic systems specifically — most engineers haven't built these before; you have. • Drive platform scalability, performance, and reliability as usage grows — cost controls, concurrency, multi-tenant isolation, and infra choices that hold up under real production load. • Experience with building, deploying and working hands on with Kubernetes environments • Support production issues across the full stack — frontend, backend, infra, and agent behavior alike: investigate, root-cause, and close the loop with tests, evals, and monitoring so the same failure doesn't recur. • Knowledge of tools such as Splunk, AppDynamics, LangSmith , Arize . • Build and maintain modern web technologies across the product: performant, accessible React/TypeScript interfaces, well-designed REST/ GraphQL APIs, and the infrastructure that serves them at scale. • Partner directly with product and design to translate ambiguous 'make the agent do X' requests into scoped, testable technical plans.

🎯 Exigences

• 8+ years of professional software engineering experience, with demonstrated full-stack ownership (backend services, APIs, and frontend interfaces). • Must have taken several Web / agentic applications to production • 2+ years hands-on experience building and operating LLM/agent-powered applications in production — real users, real load, real failure modes, not just a prototype. • Hands-on experience with CopilotKit (or comparable in-app agent UI frameworks) — shared state, generative UI, human-in-the-loop patterns, frontend action/tool wiring. • Experience building or operating Deep Agents -style systems: multi-step planning, sub-agent orchestration, long-running or asynchronous agent tasks. • Practical experience with LangSmith (or equivalent) for tracing, evaluation, and debugging LLM/agent behavior in production. • Hands-on experience with LangGraph for agent orchestration — building, debugging, and scaling multi-step agent graphs in production. • Strong, current web technologies experience — React , modern component architecture, browser performance, and accessibility — paired with backend skills in Java and Python , and experience designing APIs that connect the two layers cleanly. • Demonstrated technical leadership: design reviews, mentoring, and being the escalation point when things break in production. • Experience working on a platform team — building capabilities and tooling that other engineering teams build on top of, not just single-product feature work. • Proven ability to manage and context-switch across multiple concurrent projects and stakeholders without dropping the details. • Strong communication skills, written and verbal — this role requires translating technical tradeoffs for engineers, product, and leadership alike, and communication is treated as a core competency, not a soft nice-to-have. • Out-of-the-box thinker who can move quickly — comfortable making sound calls with incomplete information and iterating rather than waiting for the perfect plan. • Solid grasp of LLM fundamentals: prompt engineering, RAG, tool/function calling, context management, and the failure modes specific to non-deterministic systems.

🏖️ Avantages

• medical, dental, and vision coverage • paid time off • retirement savings options • wellness programs • other resources, based on eligibility