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About the Role

Lead the architecture of AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build critical system components. You will lead through technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment.

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.

Requirements

• 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.
• Deep 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.
• Experience taking AI products from concept through production deployment and long-term operational ownership.
• Experience developing AI systems where LLMs are part of critical decision-support or operational workflows.
• Expertise in evaluation frameworks, benchmark datasets, regression testing, model quality measurement, and human review processes.
• Experience with agentic systems, Model Context Protocol (MCP), workflow orchestration, multi-step reasoning frameworks, and AI observability platforms.
• Experience with React, Next.js, modern frontend technologies, and full-stack application development.
• Experience deploying and managing workloads using Kubernetes, Docker, modern CI/CD platforms, and cloud-native technologies.
• Experience with Google Cloud Platform, Azure, AWS, Vertex AI, or comparable AI and cloud infrastructure platforms.
• Experience working in highly regulated industries such as healthcare, financial services, or government.
• Knowledge of privacy, compliance, security, and governance frameworks impacting AI and data-driven applications.
• Experience implementing AI-assisted development practices that improve engineering productivity and delivery speed.
• Excellent communication, collaboration, problem-solving, and leadership skills.
• Lead through technical excellence, sound engineering judgment, and hands-on execution.
• Establish standards that drive consistency, reliability, and quality across the engineering organization.
• Influence architectural direction while balancing innovation with operational stability.
• Foster a culture of ownership, continuous learning, mentorship, and accountability.
• Drive alignment across teams and stakeholders to ensure successful delivery of strategic initiatives.
• Passionate about building production-grade AI systems where correctness, transparency, and reliability matter.
• Enjoy solving difficult engineering problems, making thoughtful architectural decisions, and helping teams deliver high-impact solutions.
• Comfortable defining system architecture, mentoring engineers, reviewing designs, responding to production incidents, and writing code for the most critical parts of the platform.
• Responsible handling of sensitive and protected data is a fundamental requirement and a core part of our engineering culture.
• Commitment to building secure, compliant, auditable, and trustworthy AI systems.

Skills

• AI
• LLMs
• Python
• TypeScript
• JavaScript
• React
• Next.js
• Docker
• Kubernetes
• CI/CD
• GCP
• Azure
• AWS
• Vertex AI
• RAG
• Agentic workflows
• Evaluation frameworks
• System architecture
• Distributed systems
• APIs
• Data platforms
• Cloud-native applications
• Reliability engineering
• System performance
• Scalability
• Operational excellence
• Privacy
• Security
• Governance
• Compliance

Location

• Remote
• Hybrid

Work Type

• Hybrid
• Full-time

Experience Level

• Lead
• 8+ years of software engineering experience

Education Level

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Salary/Compensations

• $170,800 - $234,800 per year

Benefits

• Medical benefits
• Dental benefits
• Vision benefits
• 401(k) retirement savings plan
• Time off
• Paid time off
• Company and personal holidays
• Paid parental leave
• Paid caregiver leave
• Short-term disability
• Long-term disability
• Life insurance
• Bonus incentive plan

About the Company

• Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large.

Equal Opportunity

• It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.