Distinguished Engineer, AI Adoption

Elevance Health

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Chicago, IL
Salary
$254,584–$381,876 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $218k
This role $318k
$136k most similar roles pay here $408k

This role pays more than 89% of similar roles. Most pay $162,000–$274,405 — the shaded band above. At the midpoint, this role pays about $318k versus about $218k for comparable roles.

Based on 240 similar postings.

Employer

About Elevance Health

Elevance Health (formerly Anthem, Inc.) is a leading American managed healthcare company and the largest for-profit entity in the Blue Cross Blue Shield Association, serving approximately 115 million people through health plans and Carelon services.

Elevance Health currently has 11 open roles on FindRole.

Listed pay typically runs $236,396–$339,618 across 6 roles with salary data.

Most-posted roles

View all roles at Elevance Health

At a glance

TL;DR · Distinguished Engineer, AI Adoption

The Distinguished Engineer - AI Adoption serves as a hands-on technical leader responsible for accelerating enterprise adoption of artificial intelligence by evaluating emerging technologies and designing reusable frameworks. This role involves partnering with internal teams and external vendors to assess capabilities, develop prototypes, and establish repeatable engineering patterns for high-value use cases. The individual will build agentic workflows, LLM applications, retrieval-augmented generation, and AI-assisted engineering tools while defining enterprise-wide standards for model selection, guardrails, and deployment. Key technical requirements include proficiency in Python or Java, experience with microservices, event-driven architectures, and modern DevOps practices. The role addresses the challenge of transitioning experimental AI ideas into scalable production environments by creating decision matrices and technical accelerators across cloud platforms to solve complex business problems through automated systems and intelligent decision support.

What does a Engineer earn?

Median $185000 from 256 postings across 54 companies.

See salary data

What you'll do

  • Evaluate emerging AI technologies, vendor platforms, and foundation models through hands-on testing and technical assessments.
  • Translate business problems into technical designs for LLM applications, agentic workflows, and retrieval-augmented generation.
  • Develop prototypes, proof of concepts, and technical accelerators to move AI projects from experimentation to production.
  • Create reusable engineering patterns, reference architectures, and design systems for enterprise-wide AI adoption.
  • Establish decision matrices and evaluation criteria to select the best tools based on cost, performance, and security.
  • Define enterprise standards for API patterns, model selection, guardrails, and deployment models across cloud environments.
  • Provide technical leadership in building and testing AI solutions using microservices and event-driven architectures.
  • Communicate complex trade-offs and strategic recommendations to senior technology and business leaders regarding AI investments.

What we're looking for

  • Bachelor's degree in Information Technology, Computer Science, Engineering, or a related field.
  • Minimum of 15 years of experience in software engineering including leading and designing distributed systems and large-scale architectures.
  • Experience developing and maintaining software solutions using Python, Java, or comparable object-oriented programming languages.
  • Experience designing and implementing APIs, microservices, event-driven architectures, and applying cloud, CI/CD, and DevOps practices.
  • Experience evaluating and implementing AI solutions from multiple vendors, including foundation models and orchestration frameworks (preferred).
  • Strong understanding of AI adoption strategies, including use case discovery and production-readiness planning (preferred).
  • Experience developing agentic AI frameworks, RAG patterns, and prompt strategies (preferred).
  • Proven ability to influence executives and stakeholders through technical credibility and clear communication (preferred).

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