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About This Role
Distinguished AI Engineer
Location: This role requires associates to be in-office 3 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office.
Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.
The Distinguished AI Engineer will be responsible for leading the design, development, and deployment of large-scale, production-grade artificial intelligence (AI) systems and platforms that enable enterprise-wide innovation and modernization.
How you will make an impact:
- Architect and deliver scalable, resilient AI solutions leveraging technologies such as agentic systems, large language models (LLMs), 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 (SDLC) 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.
Minimum Requirements:
- Requires a Bachelor’s degree in Computer Science, Information Technology, or related field and a minimum of 15 years of experience in software engineering, deep expertise in distributed systems and large-scale architecture, or any combination of education and experience, which would provide an equivalent background.
- Experience delivering production-grade AI/ML systems at scale, building agentic systems or complex LLM-based applications, modernizing large, complex legacy systems, and delivering high-quality systems also required.
- Strong programming expertise in Python, Java, or similar required.
- Deep experience with APIs, microservices, and event-driven architectures, cloud platforms, and CI/CD and DevOps practices required.
Preferred Skills, Capabilities and Experiences:
- Advanced experience designing and leading distributed systems and large-scale architectures is strongly preferred.
- Experience establishing enterprise technology standards and influencing technical direction across multiple teams or business domains is preferred.
- Experience serving as a technical authority for software engineering practices, architecture, platform strategy, and modern application architectures, including APIs, microservices, cloud technologies, and DevOps practices, is strongly preferred.
- Experience delivering production-grade AI/ML systems at scale, building agentic systems or complex LLM-based applications, modernizing large, complex legacy systems, and delivering high-quality systems is preferred.
- Strong programming expertise in Python, Java, or similar technology is preferred.
- Deep experience with APIs, microservices, and event-driven architectures, cloud platforms, and CI/CD and DevOps practices is preferred.
For candidates working in person or virtually in the below location, the salary range for this specific position is $254,584 to $416,592.*
Location: California, Washington, Illinois.
In addition to your salary, Elevance Health offers benefits such as a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). The salary offered for this specific position is based on a number of legitimate, non-discriminatory factors set by the Company. The Company is fully committed to ensuring equal pay opportunities for equal work regardless of gender, race, or any other category protected by federal, state, and local pay equity laws.
- The salary range is the range Elevance Health in good faith believes is the range of possible compensation for this role at the time of this posting. This range may be modified in the future and actual compensation may vary from posting based on geographic location, work experience, education, and/or skill level. Even within the range, the actual compensation will vary depending on the above factors as well as market/business considerations. No amount is wages or compensation until such amount is earned, vested, and determinable under the terms and conditions of the applicable policies and plans. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.
Please be advised that Elevance Health only accepts resumes for compensation from agencies that have a signed agreement with Elevance Health. Any unsolicited resumes, including those submitted to hiring managers, are deemed to be the property of Elevance Health.
Who We Are
Elevance Health is a health company dedicated to improving lives and communities – and making healthcare simpler. We are a Fortune 25 company with a longstanding history in the healthcare industry, looking for leaders at all levels of the organization who are passionate about making an impact on our members and the communities we serve.
How We Work
At Elevance Health, we are creating a culture that is designed to advance our strategy but will also lead to personal and professional growth for our associates. Our values and behaviors are the root of our culture. They are how we achieve our strategy, power our business outcomes and drive our shared success - for our consumers, our associates, our communities and our business.
We offer a range of market-competitive total rewards that include merit increases, paid holidays, Paid Time Off, and incentive bonus programs (unless covered by a collective bargaining agreement), medical, dental, vision, short and long term disability benefits, 401(k) +match, stock purchase plan, life insurance, wellness programs and financial education resources, to name a few.
Elevance Health operates in a Hybrid Workforce Strategy. Unless specified as primarily virtual by the hiring manager, associates are required to work at an Elevance Health location at least once per week, and potentially several times per week. Specific requirements and expectations for time onsite will be discussed as part of the hiring process.
The health of our associates and communities is a top priority for Elevance Health. We require all new candidates in certain patient/member-facing roles to become vaccinated against COVID-19 and Influenza. If you are not vaccinated, your offer will be rescinded unless you provide an acceptable explanation. Elevance Health will also follow all relevant federal, state and local laws.
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 should submit the Accessibility Accommodation Request Form and a member of the team will be in contact.
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.
Prospective employees required to be screened under Florida law should review the education and awareness resources at HB531 | Florida Agency for Health Care Administration.
Salary Context
This $254K-$416K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 2094 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 10,827 AI roles we're tracking, AI/ML Engineer positions make up 77% of the market. At Elevance Health, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,160 based on 13,809 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($335K) sits 58% above the category median. Disclosed range: $254K to $416K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
Elevance Health AI Hiring
Elevance Health has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Indianapolis, IN, US. Compensation range: $416K - $416K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (122) are outnumbered by mid-level (5,256) and senior (3,922) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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