Distinguished Engineer - AI Adoption

Distinguished Engineer – AI Adoption Location: Chicago, IL. Salary range: $254,584 to $381,876. Hybrid/Virtual work policy: Candidates must be within reasonable commuting distance unless accommodation is granted as required by law. How you will make an impact Partner with business units, engineering teams, product leaders, architecture, security, legal, compliance, and procurement to identify, evaluate, and implement practical AI solutions. Translate business problems into AI‑enabled solution designs, including agentic workflows, LLM applications, retrieval‑augmented generation, automation, decision support, and AI‑assisted engineering capabilities. Evaluate AI vendors, platforms, foundation models, agentic tools, orchestration frameworks, and emerging AI capabilities through hands‑on testing, proof of concepts, benchmarks, and technical assessments. Establish decision matrices and evaluation criteria to help teams select the right AI tools, models, platforms, and vendors based on use case fit, cost, performance, security, scalability, integration complexity, reliability, compliance, and Responsible AI considerations. Design and build reusable agentic frameworks, reference architectures, design patterns, prompts, orchestration approaches, and integration models that business units can adopt and extend. Develop prototypes, proof of concepts, and technical accelerators that demonstrate new AI ideas, validate business value, reduce uncertainty, and create a path from experimentation to production. Define enterprise‑wide AI adoption patterns, including vendor integration standards, API patterns, model selection guidance, data access approaches, observability, guardrails, evaluation practices, and deployment models. Provide hands‑on engineering leadership in building and testing AI solutions across cloud platforms, enterprise systems, APIs, microservices, event‑driven architectures, and modern DevOps environments. Stay current on the AI vendor landscape, emerging model capabilities, agentic frameworks, industry trends, and enterprise AI patterns, and translate those insights into actionable recommendations. Influence senior technology and business leaders by clearly communicating tradeoffs, risks, implementation options, and strategic recommendations for AI investments. Minimum Requirements Requires a bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field and a minimum of 15 years of experience in software engineering, including leading, designing, implementing, and operating distributed systems and large‑scale architectures, or equivalent education and experience. Experience designing, developing, and maintaining software using Python, Java, or comparable object‑oriented programming languages is required, as is experience designing and implementing APIs, microservices, event‑driven architectures, and applying cloud, CI/CD, and DevOps practices. Preferred Skills, Capabilities and Experiences Experience evaluating and implementing AI solutions from multiple vendors, including foundation model providers, cloud AI platforms, AI coding tools, agentic platforms, orchestration frameworks, and enterprise AI products. Strong understanding of AI adoption strategies, including use case discovery, proof‑of‑concept development, vendor assessment, solution selection, technical enablement, and production‑readiness planning. Experience developing agentic AI frameworks, reusable design patterns, prompt strategies, orchestration flows, tool‑calling patterns, RAG patterns, workflow automation, and human‑in‑the‑loop models. Ability to create decision matrices, technical scorecards, benchmark approaches, and recommendation frameworks for selecting AI tools, models, platforms, and vendors. Proven ability to rapidly prototype new ideas, test emerging technologies, validate feasibility, and convert successful experiments into scalable engineering patterns. Experience mentoring engineering teams and creating enablement materials, reference implementations, reusable frameworks, and adoption playbooks for enterprise AI. Demonstrated ability to influence executives, engineering leaders, architects, vendors, and cross‑functional stakeholders through technical credibility, clear communication, and hands‑on delivery. Experience including hands‑on technical leadership in designing, evaluating, prototyping, or delivering enterprise‑scale AI, cloud, platform, integration, or distributed systems solutions. Elevance Health is an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to age, citizenship status, color, creed, disability, ethnicity, genetic information, gender (including gender identity and gender expression), marital status, national origin, race, religion, sex, sexual orientation, veteran status or any other status or condition protected by applicable federal, state, or local laws. Applicants who require accommodation to participate in the job application process may contact View email address on click.appcast.io for assistance. Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws, including, but not limited to, the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act. #J-18808-Ljbffr Elevance Health