Lead AI Engineer — Production-Grade LLM Systems

Humana

New York (NY)

Hybrid

USD 171,000 - 235,000

Full time

14 days+

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Job summary

Humana is seeking a Lead AI Applied Engineer to own the architecture and delivery of AI-enabled products and platforms that transform clinical documents into actionable data. You will lead through technical excellence, stay hands-on in coding, and guide teams to build reliable, auditable AI solutions in a highly regulated healthcare environment.

You will define architectural direction, establish engineering standards, and mentor engineers while partnering with stakeholders to meet regulatory

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
8+ years of software engineering experience, including experience designing and operating production systems at scale.
Proven track record of delivering AI-enabled products or platforms into production environments.
Hands-on experience integrating and operating LLMs within business-critical workflows.
Experience designing systems that leverage structured outputs, tool calling, retrieval-augmented generation (RAG), agentic workflows, orchestration frameworks, and evaluation pipelines.
Experience making architectural decisions for systems where AI is a core component of the product experience.
Demonstrated success leading technical initiatives across engineering teams, including architecture reviews, technical planning, mentoring, and delivery execution.
Strong programming skills in Python and/or TypeScript/JavaScript.
Experience designing and operating distributed systems, APIs, data platforms, and cloud-native applications.
Strong understanding of reliability engineering, system performance, scalability, and operational excellence.
Ability to balance technical tradeoffs involving quality, latency, cost, security, and maintainability.

Responsibilities

Own the architecture, design, and evolution of full-stack AI applications, including LLM pipelines, retrieval systems, agentic workflows, human-in-the-loop processes, and supporting platform services.
Design and implement scalable AI solutions that prioritize reliability, accuracy, auditability, performance, and cost efficiency.
Build and maintain the most complex and high-risk system components where architecture and implementation decisions have significant business impact.
Define and enforce engineering standards for AI systems, including evaluation methodologies, structured outputs, observability, testing, fallback strategies, latency optimization, and cost controls.
Lead technical design reviews and guide architecture decisions related to platform capabilities, AI systems, integrations, infrastructure, and software patterns.
Evaluate and recommend technologies, frameworks, AI models, and third‑party solutions based on technical and business requirements.
Translate ambiguous business goals into clear technical strategies, roadmaps, and executable workstreams.
Provide technical leadership across multiple projects, ensuring alignment with architectural standards and long‑term platform objectives.
Mentor and coach engineers through design reviews, code reviews, pair programming, and technical guidance.
Partner with product, engineering, clinical, and operational stakeholders to deliver solutions that meet business and regulatory requirements.
Own operational excellence, including deployment strategies, monitoring, incident management, and production reliability.
Ensure all solutions comply with privacy, security, governance, and audit requirements within a regulated healthcare environment.