Distinguished Engineer

Elevance Health•Indianapolis, IN

3d•Hybrid

About The Position

The Distinguished Engineer leads the design, development, and deployment of large-scale, production-grade artificial intelligence (AI) systems and platforms that enable enterprise-wide innovation and modernization. The role combines hands-on software engineering with enterprise technical leadership, setting direction for architecture, integration, and reusable platform capabilities. It also guides modernization of legacy systems, AI-enabled software development practices, and responsible governance of AI systems. The engineer partners with engineering teams and stakeholders to advance AI-assisted development and improve system performance and productivity. This position provides technical leadership and mentorship, develops engineering talent, and influences enterprise technology decisions. It requires a bachelor’s degree in a relevant field and at least 15 years of software engineering experience, including leadership in distributed systems and large-scale architectures, or an equivalent combination of education and experience. The role is hybrid and requires associates to work in-office three days per week. Candidates must be within a 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 hands-on software engineering expertise, including architecting, writing, optimizing, and delivering high-quality production code.
Ability to set high engineering standards and mentor senior engineers while developing technical talent and organizational engineering capabilities.
Deep understanding of AI, generative AI, agentic systems, LLMs, intelligent automation, and modern data architectures.
Hands-on experience applying emerging technologies to production-ready solutions that improve business outcomes, operational efficiency, customer experiences, and decision-making.
Ability to understand complex business domains and connect business processes, products, data, systems, and technology across organizational boundaries.
Experience translating end-to-end business journeys and enterprise challenges into scalable, practical technology solutions.
Experience building and evolving enterprise technology capabilities as products, including long-term vision, roadmaps, reusable platforms, architectural standards, and investment priorities.
Focus on scalability, simplicity, engineering efficiency, and measurable business value.
Healthcare payer and provider ecosystem experience, ideally in provider onboarding, credentialing, contracting, provider data management, network management, provider performance, interoperability, or related capabilities.
Demonstrated ownership, sound judgment, and ability to navigate ambiguity, dependencies, and organizational complexity to deliver results.
Ability to communicate technical and business concepts to senior executives, articulate technology strategy and tradeoffs, influence enterprise decisions without direct authority, and build alignment around strategic priorities.
Ability to build cross-functional partnerships, mobilize diverse teams, challenge conventional thinking constructively, and drive shared accountability for enterprise 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 while influencing enterprise technology decisions through deep expertise and hands-on engineering.
Personally drive complex technology initiatives from problem definition and architecture through development, implementation, production deployment, and measurable outcomes.
Build trusted partnerships across business, product, engineering, architecture, data, operations, security, and other enterprise functions.