Senior AI Solutions Engineer (Engineer Senior)

Elevance Health • Atlanta, GA

3d • Hybrid

About The Position

The Senior AI Solutions Engineer will build and scale intelligent systems intended to improve healthcare outcomes. The role designs, builds, and deploys machine learning and large language model (LLM)-based systems, taking models from experimentation through production within an assigned client group, business unit, or corporate department and across customer technology platforms. It also delivers end-to-end application and system development and maintenance on complex, multi-technology platforms.

The engineer works with product, data, engineering, architecture, and business teams to translate business problems into scalable AI/ML solutions. The role develops production-ready AI/ML services and systems, provides technical leadership and guidance, and supports operational monitoring and reliability. It may include mentoring colleagues and leading multiple small-to-medium-sized projects.

This hybrid role requires associates to work in-office 1–2 days per week. The ideal candidate can report to the Pulse Point location in Atlanta, Georgia; alternate locations may be considered for candidates within commuting distance of an office. Candidates outside reasonable commuting distance generally will not be considered unless an accommodation is granted as required by law.

Requirements

• BA/BS degree in Information Technology, Computer Science, or a related field, and at least 5 years of related experience; alternatively, an equivalent combination of education and experience.
• Experience working with multi-dimensional platforms and business and technical applications.
• Ability to work in a hybrid arrangement, with in-office attendance 1–2 days per week and reasonable commuting distance from an office, unless an accommodation is granted as required by law.

Nice To Haves

• Master’s or PhD degree.
• Advanced Python skills for machine learning and data processing.
• Experience across the full machine learning lifecycle, including development, deployment, and monitoring.
• Hands-on experience with LLMs, embeddings, RAG, or modern NLP techniques using vector search technologies such as OpenSearch.
• Experience building production AI systems, including APIs, pipelines, and microservices.
• Experience designing evaluation frameworks for ML/LLM systems.
• Familiarity with responsible AI principles, including fairness, explainability, and privacy.
• Experience with cloud-based ML platforms and scalable architectures, such as AWS Bedrock or equivalent AI model cloud providers.
• Healthcare domain experience, including familiarity with data privacy and regulatory requirements.
• Multi-database and/or multi-language experience.
• Experience mentoring others, leading multiple small projects, and providing troubleshooting support.

Responsibilities

• Maintain active relationships with product, data, engineering, architecture, and business teams to translate business problems into scalable AI/ML solutions.
• Apply AI/ML capabilities and modern AI tools to business problems, healthcare outcomes, and adoption across business workflows, digital products, and enterprise applications.
• Own the change request process and coordinate with other teams as needed.
• Provide technical advice and contribute to technical decisions affecting cross-functional teams, including AI/ML and advanced analytics solutions.
• Research and propose technologies, stay current with AI developments, and identify relevant enterprise use cases.
• Design, build, and deploy end-to-end ML and LLM-based systems, including data pipelines, models, prompts, APIs, and monitoring.
• Develop, evaluate, deploy, and monitor machine learning models for predictive, classification, optimization, personalization, and decision-support use cases.
• Build applied AI solutions such as semantic search, RAG pipelines, and embedding-based systems.
• Develop production-ready AI/ML services, APIs, pipelines, and reusable components; improve production performance, scalability, reliability, usability, and operational readiness.
• Conduct technical design and code reviews; provide technical leadership through solution design, best practices, troubleshooting, and mentoring junior team members.
• Assess status and support data information planning.
• Coordinate on-call support and ensure effective system monitoring, including AI/ML model performance and reliability.
• Mentor others and potentially lead multiple or small-to-medium-sized projects.
• Influence engineering standards and technical direction.
• Identify strategies for technical problems affecting the team, communicate standards, and gain buy-in on solutions.

Benefits

• Merit increases
• Paid holidays
• Paid Time Off
• Incentive bonus programs (unless covered by a collective bargaining agreement)
• Medical benefits
• Dental benefits
• Vision benefits
• Short- and long-term disability benefits
• 401(k) with company match
• Stock purchase plan
• Life insurance
• Wellness programs
• Financial education resources

What This Job Offers

• Job Type: Full-time
• Career Level: Senior