Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

This role requires a leader who can define the vision for AI utilization and demonstrate its viability through hands-on engineering. You will be responsible for building the platform that transforms clinical documents into actionable data using LLMs, supporting decisions that impact healthcare outcomes.

Responsibilities

• Define and drive the long-term technical strategy, reference architecture, and technology roadmap for AI-enabled products and platforms.
• Establish architectural patterns and best practices for retrieval systems, LLM orchestration, agentic workflows, human-in-the-loop processes, evaluation frameworks, and AI governance.
• Lead organization-wide technical decision-making regarding model strategy, vendor selection, platform investments, build-versus-buy decisions, and shared infrastructure capabilities.
• Design and champion scalable architectures that balance reliability, performance, security, compliance, maintainability, and cost efficiency.
• Establish engineering standards for evaluation, observability, model lifecycle management, responsible AI practices, and operational excellence.
• Build prototypes, proofs of concept, and reference implementations that de-risk emerging technologies and strategic platform investments.
• Lead cross-functional architecture reviews and provide technical guidance across multiple engineering teams.
• Mentor Lead Engineers, Senior Engineers, and emerging technical leaders through architecture reviews, design feedback, coaching, and technical sponsorship.
• Develop and communicate technical roadmaps aligned with business strategy and organizational objectives.
• Partner with executive leadership to translate business priorities into technical strategies and communicate technical opportunities, risks, and tradeoffs.
• Represent engineering in strategic vendor evaluations, compliance discussions, governance reviews, and enterprise planning initiatives.
• Drive adoption of common platforms, standards, and engineering practices across teams.
• Ensure AI systems are designed and operated in accordance with privacy, security, compliance, governance, and auditability requirements.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 12+ years of software engineering experience, including extensive experience designing and operating large-scale distributed systems.
• Proven track record of designing, delivering, and operating production AI-enabled platforms or products at enterprise scale.
• Deep expertise in large language model technologies, AI platform design, retrieval-augmented generation (RAG), agentic systems, orchestration frameworks, evaluation methodologies, and AI operations.
• Extensive experience designing cloud-native architectures and highly scalable, resilient systems.
• Demonstrated ability to define technical direction that influenced teams, organizations, or product portfolios beyond direct reporting relationships.
• Experience establishing engineering standards, architectural frameworks, or technical platforms that have been successfully adopted across multiple teams.
• Strong understanding of AI operational challenges, including model reliability, latency, cost optimization, governance, observability, and risk management.
• Demonstrated success influencing executive stakeholders and driving organizational decisions through technical leadership and evidence-based recommendations.
• Expert-level proficiency in Python and/or TypeScript/JavaScript.
• Ability to prototype, debug, review, and contribute code across multiple layers of the technology stack.
• Experience leading AI platform strategy across multiple business units or product organizations.
• Experience developing enterprise standards for AI evaluation, testing, observability, governance, and responsible AI practices.
• Expertise evaluating and managing AI vendor ecosystems across multiple model providers and platform technologies.
• Experience building shared AI infrastructure and platform capabilities consumed by multiple engineering teams.
• Experience with agentic architectures, Model Context Protocol (MCP), workflow orchestration, autonomous systems, and emerging AI frameworks.
• Experience operating AI systems at significant scale while managing performance, reliability, and cost tradeoffs.
• Experience working in regulated industries such as healthcare, financial services, life sciences, or government.
• Deep understanding of privacy, security, compliance, governance, and risk management requirements in highly regulated environments.
• Experience driving adoption of AI-assisted software development practices across engineering organizations.
• Experience advising executive leadership on emerging technologies, platform strategy, and enterprise architecture decisions.
• Exceptional communication, leadership, collaboration, and strategic problem-solving skills.
• Serve as the highest-level technical authority within the AI Applied Engineering organization.
• Influence organizational outcomes through technical excellence, credibility, and demonstrated results rather than formal authority.
• Balance innovation with operational discipline and long-term sustainability.
• Establish scalable technical standards that enable teams to move faster while maintaining quality and reliability.
• Drive alignment across engineering, product, business, clinical, compliance, and executive stakeholders.
• Build organizational capability by mentoring and developing the next generation of technical leaders.
• Foster a culture of engineering rigor, continuous learning, accountability, and responsible AI development.

Skills

• TypeScript
• React / Next.js
• Python
• PostgreSQL
• Gemini on Vertex AI
• OCR and Document AI technologies
• Docker
• Kubernetes
• Modern CI/CD platforms and tooling
• Large language model technologies
• AI platform design
• Retrieval-augmented generation (RAG)
• Agentic systems
• Orchestration frameworks
• Evaluation methodologies
• AI operations
• Cloud-native architectures
• Highly scalable, resilient systems
• Privacy
• Security
• Compliance
• Governance
• Auditability
• Responsible AI practices
• Operational excellence
• Model reliability
• Latency
• Cost optimization
• Observability
• Risk management
• Communication
• Leadership
• Collaboration
• Strategic problem-solving

Location

• Talent markets

Work Type

• Hybrid

Experience Level

• Principal
• 12+ 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

• $206,600 - $284,300 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

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, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.