Distinguished Engineer

Elevance Health•Atlanta, GA

1d•Hybrid

About The Position

The Distinguished Engineer leads the design, development, and deployment of large-scale, production-grade artificial intelligence systems and platforms that enable enterprise-wide innovation and modernization. The role sets technical direction and standards, leads AI-driven modernization of legacy systems, and advances AI-enabled software development practices. It also partners with engineering teams and stakeholders to support adoption, improve system performance and productivity, and influence enterprise technology decisions through hands-on expertise and mentorship. This is a hybrid role requiring associates to work in-office three days per week. Candidates must live within reasonable commuting distance of a posting location unless an accommodation is granted as required by law. The position is not eligible for current or future visa sponsorship.

Requirements

Bachelor’s degree in information technology, computer science, engineering, or a related field, and at least 15 years of software engineering experience; an equivalent combination of education and experience may be considered.
Experience leading, designing, implementing, and operating distributed systems and large-scale architectures.
Experience designing, developing, and maintaining software solutions using Python, Java, or comparable object-oriented programming languages.
Experience designing and implementing APIs, microservices, and event-driven architectures.
Experience applying cloud, CI/CD, and DevOps practices.

Nice To Haves

Exceptional software engineering expertise and demonstrated ability to architect, build, optimize, and deliver production solutions, set high engineering standards, and develop technical talent.
Deep understanding of AI, generative AI, agentic systems, large language models, intelligent automation, and modern data architectures.
Experience applying AI technologies to improve decision-making, member engagement, and health outcomes, including trusted and safe AI-enabled experiences.
Ability to connect business processes, products, data, systems, and technology across organizational boundaries and translate complex challenges into scalable solutions informed by behavioral, social, and population-health insights.
Experience establishing technology vision, roadmaps, reusable platforms, architectural standards, and investment priorities, with a focus on scalability, simplicity, experimentation, and measurable value.
Experience in behavioral science, public health, population health, health psychology, epidemiology, or related disciplines.
Knowledge of behavior change, social determinants of health, population segmentation, health equity, and evidence-based interventions.
Experience translating behavioral insights into scalable digital, AI, and human interventions.
Advanced training in a relevant discipline or equivalent experience.
Exceptional ability to translate technical, behavioral, and public health concepts into clear technology strategy, influence enterprise decisions, communicate tradeoffs, and build executive alignment.
Proven ability to build cross-functional partnerships and bring multidisciplinary teams together around shared outcomes.

Responsibilities

Architect and deliver scalable, resilient AI solutions using technologies such as agentic systems, large language models, distributed systems, and event-driven architectures.
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 adoption of AI-assisted development and drive continuous improvement in system performance and productivity.
Provide technical leadership and mentorship, and influence enterprise technology decisions through deep expertise and hands-on engineering.
Drive complex initiatives from problem definition and architecture through implementation and production, including translating behavioral and population-health evidence into scalable interventions and measurable outcomes.
Build trusted partnerships across product, engineering, data, operations, clinical, behavioral health, population health, care management, and analytics.