Job description

Job Title: Senior AI Engineer (LLM / Agent Systems) Role Overview Join a high-growth, venture-backed healthcare AI company building next-generation technology to transform clinical and operational workflows across post-acute care. The platform combines proprietary sensing technology, predictive analytics, and emerging AI capabilities to proactively identify risk and improve patient outcomes at scale. The company is now expanding into a new AI-driven product layer focused on LLM-powered workflows and agent-based systems that unify clinical, operational, and financial data into a single intelligent interface. Think of it as a domain-specific AI platform enabling real-time decision-making across healthcare environments. This role sits at the intersection of engineering, product, and customer delivery. You will design and deploy production-grade AI agents, work directly with customers, and play a key role in shaping how AI is applied in real-world clinical settings. Key Responsibilities: • Design and deploy LLM-powered agents and workflows for real-world use cases (e.g., automation, insights, operational decisioning) • Translate ambiguous customer requirements into scalable, production-ready AI systems • Build and integrate pipelines across APIs, data platforms, and external systems (REST, webhooks, event streams) • Configure and optimize RAG pipelines, vector databases, and context management systems • Partner with Sales during pre-sales to prototype solutions, whiteboard architectures, and define implementation scope • Own end-to-end delivery from initial prototype through production deployment and iteration • Analyze system performance (accuracy, hallucination rates, outcomes) and continuously improve models and workflows • Collaborate cross-functionally with engineering, product, and customer stakeholders • Travel to customer sites (~25%) to support deployments, training, and executive presentations • Identify expansion opportunities and support additional use cases post-deployment Education & Qualifications: • 5–10+ years of experience in software engineering, AI engineering, solutions engineering, or similar hands-on technical roles • Strong experience building and shipping production systems (not just prototypes or research work) • Proficiency with APIs, integrations, and backend development (Python, Node.js/TypeScript, or similar) • Experience working with LLMs and modern AI tooling (OpenAI, Anthropic, or similar ecosystems) • Familiarity with agent frameworks, RAG architectures, or context orchestration systems • Ability to operate in ambiguous environments and take full ownership of outcomes • Strong communication skills with the ability to translate complex technical concepts to non-technical stakeholders • Comfortable working in a fast-paced, high-growth startup environment Preferred Experience: • Hands-on experience with tools such as LangChain, LangGraph, AutoGen, DSPy, or similar frameworks • Experience building AI systems that interact with real-world data (e.g., time-series, operational systems, or large-scale datasets) • Background in regulated environments (e.g., healthcare, fintech, or similar) • Experience owning both pre-sales and post-sales technical delivery • Exposure to enterprise system integrations (e.g., event-driven architectures, streaming, or workflow automation) • Advanced degrees (MS/PhD) from strong technical programs are valued but not required Why Us: • Opportunity to build next-generation AI systems with real-world impact at scale • Work on a new product initiative centered around LLMs, agents, and intelligent workflows • High ownership role with direct influence on product direction and customer outcomes • Fast-growing company with strong traction and significant enterprise demand • Work alongside a highly technical, mission-driven team focused on meaningful problems • Exposure to both cutting-edge AI and real-world deployment challenges Benefits and Perks: • $120k-220k DOE + bonus + equity • 100% company-paid medical, dental, and vision insurance • 401(k) with company match • Generous PTO • Paid parental leave • Commuter benefits • Professional development support • Company retreats and team events Applicants must be currently authorized to work in the United States on a full-time basis now and in the future. This position does not offer sponsorship. #LI-EC1

Requirements

Must-haves

Job Title: Senior AI Engineer (LLM / Agent Systems)
Design and deploy LLM-powered agents and workflows for real-world use cases (e.g., automation, insights, operational decisioning)
Translate ambiguous customer requirements into scalable, production-ready AI systems
Build and integrate pipelines across APIs, data platforms, and external systems (REST, webhooks, event streams)
Configure and optimize RAG pipelines, vector databases, and context management systems
Partner with Sales during pre-sales to prototype solutions, whiteboard architectures, and define implementation scope
Own end-to-end delivery from initial prototype through production deployment and iteration
Analyze system performance (accuracy, hallucination rates, outcomes) and continuously improve models and workflows
Collaborate cross-functionally with engineering, product, and customer stakeholders
Travel to customer sites (~25%) to support deployments, training, and executive presentations
Identify expansion opportunities and support additional use cases post-deployment
5–10+ years of experience in software engineering, AI engineering, solutions engineering, or similar hands-on technical roles
Strong experience building and shipping production systems (not just prototypes or research work)
Proficiency with APIs, integrations, and backend development (Python, Node.js/TypeScript, or similar)
Experience working with LLMs and modern AI tooling (OpenAI, Anthropic, or similar ecosystems)
Familiarity with agent frameworks, RAG architectures, or context orchestration systems
Ability to operate in ambiguous environments and take full ownership of outcomes
Strong communication skills with the ability to translate complex technical concepts to non-technical stakeholders
Comfortable working in a fast-paced, high-growth startup environment

Nice-to-haves

Hands-on experience with tools such as LangChain, LangGraph, AutoGen, DSPy, or similar frameworks
Experience building AI systems that interact with real-world data (e.g., time-series, operational systems, or large-scale datasets)
Background in regulated environments (e.g., healthcare, fintech, or similar)
Experience owning both pre-sales and post-sales technical delivery
Exposure to enterprise system integrations (e.g., event-driven architectures, streaming, or workflow automation)

Application prep

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Keywords to mirror

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Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave

Professional Development