Distinguished AI Engineer

Elevance Health•Tampa, FL

1d•Hybrid

About The Position

The Distinguished AI Engineer is a highly experienced, hands-on individual contributor who designs, builds, and scales enterprise AI solutions across machine learning, generative AI, and AI agents. The role combines deep technical expertise and business acumen to deliver production-grade AI capabilities while influencing architecture, delivery models, and engineering practices across the organization. It is a hands-on engineering position, not a pure research or management role, and includes making buy, build, and integration decisions across commercial and open-source AI solutions based on business needs, regulatory requirements, speed to value, and long-term maintainability. The position requires associates to work in an office one day per week. The ideal candidate can report to the Pulse Point location in Indianapolis, Indiana; alternate locations may be considered for candidates within commuting distance of an office. Candidates outside a reasonable commuting distance will not be considered unless an accommodation is granted as required by law. The engineer will provide technical direction, build reusable AI services and capabilities, guide implementation teams, and mentor engineers. They will help modernize legacy systems and improve software development practices using AI, while ensuring that solutions meet enterprise requirements for scalability, security, observability, governance, and maintainability.

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field and at least 15 years of experience in software engineering, with deep expertise in distributed systems and large-scale architecture; an equivalent combination of education and experience is acceptable.
Experience delivering production-grade AI/ML systems at scale.
Experience building agentic systems or complex LLM-based applications.
Experience modernizing large, complex legacy systems and delivering high-quality systems.
Strong programming expertise in Python, Java, or a similar language.
Deep experience with APIs, microservices, event-driven architectures, cloud platforms, and CI/CD and DevOps practices.

Nice To Haves

Subject matter expertise in machine learning, generative AI, and AI agents.
Experience working in a Fortune 100 regulated company, startup, and/or top-tier technology firm.
Proven success building and deploying reusable AI services at scale.
Experience operationalizing AI in production with MLOps, LLMOps, observability, and governance practices.

Responsibilities

Design, develop, and deploy enterprise AI solutions spanning traditional machine learning, generative AI, and agentic AI systems.
Architect and deliver scalable, resilient AI solutions using agentic systems, large language models, distributed systems, and event-driven architectures.
Serve as a senior hands-on contributor, technical leader, and subject matter expert across the AI development lifecycle.
Build reusable AI services, frameworks, accelerators, and reference architectures for use across multiple teams and use cases.
Partner with business domain subject matter experts, product, engineering, architecture, security, data, and business teams to translate opportunities into scalable AI solutions.
Lead buy, build, and integration decisions across commercial and open-source AI solutions, balancing speed, cost, risk, security, scalability, and strategic differentiation.
Use modern AI-assisted development tools to improve the speed, quality, and efficiency of solution delivery.
Guide implementation teams through architecture, design, model selection, evaluation, deployment, and operationalization of AI solutions.
Mentor junior AI engineers and strengthen the organization's AI engineering capabilities.
Influence technical direction across teams through expertise, credibility, and collaboration rather than formal authority.
Ensure solutions meet enterprise requirements for scalability, security, observability, governance, and maintainability.
Define enterprise-wide technical direction, including architecture patterns, integration standards, and reusable platform capabilities.
Lead AI-driven modernization of legacy systems through automated code transformation, service decomposition, and continuous optimization.
Design and implement AI-enabled software development lifecycle practices to improve engineering velocity and quality.
Establish technical standards, governance frameworks, and best practices for AI systems, including monitoring, evaluation, and responsible AI.
Partner with engineering teams and stakeholders to enable AI-assisted development adoption and continuously improve system performance and productivity.
Provide technical leadership and mentorship while influencing enterprise technology decisions through deep expertise and hands-on engineering.