Responsibilities
- Lead the design and build of advanced generative AI systems, spanning LLM-powered applications, multi-agent workflows, RAG, and domain-specific reasoning engines.
- Architect and own robust APIs and platform capabilities that bring AI to real business workflows at enterprise scale.
- Drive the engineering of high-quality data, feature, and evaluation pipelines that support reliable and continuously improving AI behavior.
- Partner with data scientists, platform engineers, and product leaders to transform conceptual ideas into resilient, testable, observable production systems.
- Set engineering standards and elevate team culture, emphasizing clarity, craftsmanship, iteration, and objective measures of excellence.
- Mentor other engineers and guide teams through complex technical decision-making.
- Serve as a thought leader on the practical application of generative AI technologies, emerging patterns, and their fit within our ecosystem.
- Champion observability, measurement, and operational excellence, ensuring deployed systems are trustworthy, maintainable, and high-performing.
- Stay at the forefront of AI/ML advancements and help the organization understand the right time, and the right way, to adopt new technologies. The successful candidate will help drive key business outcomes, including measurable improvements in healthcare delivery and member satisfaction.
Basic qualifications
- Bachelor’s or Master’s in Computer Science, Engineering, or a related quantitative field.
- 10+ years of professional software or platform engineering experience.
- Deep expertise in Python, including building production services and shared libraries used by others.
- Hands-on experience with modern AI systems, including LLM integration, RAG, embeddings, and applied generative AI patterns.
- Strong background in machine learning engineering, including model deployment, monitoring, evaluation, and lifecycle management.
- Expert-level understanding of FastAPI, Flask, or similar frameworks, and REST/gRPC service design.
- Strong proficiency with cloud-native development on AWS, GCP, or Azure.
- Minimum 5 years of containerization and orchestration experience (Docker, Kubernetes).
- Production experience with CI/CD pipelines, version control, and modern DevOps practices.
- Demonstrated ability to own large, ambiguous problems and deliver high-value, high-quality solutions.
Preferred qualifications
- Experience shaping engineering culture or influencing architectural direction across teams.
- Experience with generative AI tooling (e.g., LangChain, LlamaIndex, PydanticAI, or similar).
- Strong understanding of deep learning frameworks (PyTorch, TensorFlow).
- Experience with distributed systems (Akka, Flink, or similar).
- Prior work building platforms rather than one-off applications.
- A track record of pragmatic decision-making, balancing innovation with maintainability and long-term value.
About the company
Humana Inc. (NYSE: HUM) is committed to putting health first – for our teammates, our customers and our company. Through our Humana insurance services and 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, Medicaid, families, individuals, military service personnel, and communities at large.
Equal Opportunity Employer
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.