Advisory Services Consultant - Full Stack AI Engineer

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

We are looking for a Full Stack AI Engineer who can design, build, and operate end-to-end AI-powered applications for healthcare use cases. This role blends solid full stack engineering fundamentals with hands-on experience applying modern AI/ML and LLM technologies in production systems.

You will work across frontend, backend, and AI layers to deliver scalable, secure, and user-centric solutions, owning features from concept to production and continuously improving them using data.

• Translate functional requirements into scalable, maintainable AI components
• Design, build, and maintain end-to-end enterprise applications using modern frontend and backend frameworks
• Develop scalable backend services and APIs (REST/GraphQL) to support AI-driven use cases
• Ensure high standards for performance, reliability, security and maintainability
• Write clean, testable, well-documented code and participate in code reviews
• Design and implement AI-powered features including LLM-based workflows, retrieval-augmented generation (RAG), agents and prompt-driven systems
• Integrate AI models into applications using APIs and SDKs (open-source or enterprise-approved)
• Collaborate on model evaluation, prompt tuning, and experimentation to improve quality and accuracy
• Apply responsible AI principles including security, privacy, explainability and bias mitigation
• Ensure secure, compliant PHI/PII handling aligned with regulatory requirements
• Apply LLM Ops best practices for RAG and agentic system deployment
• Deploy and operate applications in cloud environments using CI/CD pipelines
• Monitor application and AI system performance, reliability and cost
• Troubleshoot production issues across frontend, backend and AI components
• Partner with product managers, designers and other engineers to translate business needs into technical solutions
• Contribute to architectural decisions, reusable frameworks and technical standards
• Mentor junior engineers and promote best practices across the team
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

• 7+ years of experience in full-stack software development
• Solid hands-on experience building or integrating AI/ML or LLM-based solutions, prompt engineering, RAG pipelines and/or AI agents
• Experience with APIs, databases and distributed systems
• Experience deploying AI solutions in production environments
• Experience with DevOps, CI/CD, observability and infrastructure as code
• Proficiency in frontend technologies (e.g., React, Angular, or similar)
• Proficiency in backend development (e.g., Node.js, Python, Java, or similar)
• Solid understanding of software engineering fundamentals including data structures, APIs, testing and design patterns
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn), RAG fundamentals, agent workflows and vector databases
• Knowledge of cloud platforms (Azure, AWS, or GCP)
• Background in security, compliance or regulated environments
• Solid analytical mindset and problem-solving skills
• Ability to work in fast-paced consulting and product delivery environments
• Proven clear communication with technical and non technical stakeholders
• Demonstrates passion for building AI systems that drive real world impact in healthcare