Applied AI Engineer
Responsibilities
- check_circle Design, build, and operate production services that leverage Large Language Models, RAG, and agentic workflows to solve real business problems.
- check_circle Architect and maintain scalable, well-tested APIs and backend systems that expose AI capabilities to downstream applications.
- check_circle Build and maintain robust data and inference pipelines for ingestion, processing, transformation, and serving of large datasets and model outputs.
- check_circle Own the reliability, performance, cost, and observability of deployed APIs, and pipelines (logging, metrics, tracing, alerting, evals).
- check_circle Drive engineering best practices across the team: code review, testing, CI/CD, documentation, and secure-by-default design.
- check_circle Stay current with advancements in LLMs, agent frameworks, and AI infrastructure, and translate them into pragmatic engineering improvements.
Basic qualifications
- Bachelor's Degree in a quantitative discipline (e.g., Computer Science, Software Engineering, Mathematics, or a related field) with a minimum of 5 years of professional software engineering experience; OR
- Master's Degree in a similar field with at least 3 years of relevant software engineering experience.5+ years of experience developing production Python-based applications and services intended for use by others — not just models, scripts, or analyses.
- Strong software engineering fundamentals: API and system design, data structures, testing, code review, and debugging distributed systems.
- Proficiency with API frameworks (e.g., FastAPI, Flask) and solid grasp of RESTful API design, authentication, and versioning.
- Experience building and operating backend services on cloud platforms (e.g., AWS, Google Cloud, Azure).
- 3+ years of experience with containerization and orchestration (e.g., Docker, Kubernetes).
- 2+ years of experience with CI/CD tools and pipelines, and shipping code to production on a regular cadence.
- Hands-on experience integrating Large Language Models (LLMs) into production applications — including prompt design, tool/function calling, evaluation, and cost/latency tuning.
- Strong experience with version control (Git), trunk-based or feature-branch workflows, and modern software development best practices.
- **Hands-on experience using agentic AI coding tools (e.g., Claude Code, Cursor, GitHub Copilot agents) as part of the day-to-day development workflow, including effective prompting, reviewing AI-generated code, and iterating on multi-step agent tasks.
- Experience designing and operating agentic or RAG-based systems in production (retrieval, tool use, memory, evals).
- Experience with distributed systems, event-driven architectures, or streaming platforms (e.g., Kafka).
- Familiarity with generative AI frameworks such as LangChain, LlamaIndex, or Pydantic AI.
- Familiarity with observability and evaluation tooling for LLM applications (e.g., OpenTelemetry, LangSmith, Arize, custom eval harnesses).
- Familiarity with infrastructure-as-code (e.g., Terraform, Pulumi).
- Excellent problem-solving skills and ability to work in a collaborative, fast-moving environment.
About the company
About Humana: 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. Learn more about what we offer at Humana.com and at CenterWell.com.
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.
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