Interested in this AI/ML Engineer role at Alight Solutions?
Apply Now →About This Role
Our Story
At Alight, we believe a company’s success starts with its people. Alight embraces values that come directly from our people – purposeful, human, united and growth\-minded – reflecting our inclusive culture and promise that our clients expect. We are passionate about connecting purpose with impact. Alight empowers clients to build a healthier and more financially secure workforce by unifying the benefits ecosystem across health, wealth, wellbeing, navigation, and absence management.
Our Benefits
With a comprehensive total rewards package, Alight offers programs and plans that support your mind, body, wallet, and life. Benefits include health, dental and vision coverages starting Day One. Additionally, Alight colleagues enjoy wellbeing programs, retirement plans with contribution matching, generous time off, parental leave, continuing education, and career growth opportunities – all within a thriving global organization.
Flexible Working
So that you can be your best at work and home, we consider flexible working arrangements wherever possible. Alight has been a leader in the flexible workspace and “Top 100 Company for Remote Jobs” 6 years in a row.
Great Place to Work
Thanks to the work of every colleague, Alight has received multiple awards of recognition including “Great Place to Work” for the past 7 years and Fortune’s “Best Companies to Work For.” To learn more about our company culture and awards Click Here.
We invite you to join our team! Learn more at careers.alight.com.
The Opportunity
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More than 30 million people rely on Alight to navigate the biggest decisions of their lives, across their health, their wealth, and their time away from work. Alight is seeking a Vice President of Artificial Intelligence to lead how we build, deploy, and scale AI across our products, services, and operations, and to use agentic AI to transform how people understand and act on their benefits.
The first generation of AI capabilities is already in production. This leader inherits that foundation and is accountable for its next phase, scaling it into a coherent capability across the company. The opportunity is grounded in a combination few companies hold:
- Deep domain expertise in health, wealth, and benefits administration
- Rich data on the moments that matter to participants
- Operational workflows where intelligent automation can change outcomes
- An established enterprise where trust, privacy, and responsible AI are essential
The role reports to the senior executive leading Alight's data, AI, and transformation agenda, with direct access to executive leadership and partnership across product, technology, operations, commercial, risk, and compliance. It carries the visibility, sponsorship, and accountability of a true enterprise leadership role.
If you want to lead AI where the problems are complex, the data is consequential, trust matters, and the work reaches a population that depends on it, this is that opportunity.
What You Will Lead
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Set the AI direction
Define a clear and differentiated AI strategy rooted in the problems Alight is uniquely positioned to solve, and translate it into a focused portfolio.
- Make explicit choices about where Alight builds, partners, buys, and stops investing
- Concentrate investment where it delivers the most value, governing for cost per outcome as the platform matures
- Mature the reference architecture into the operating standard, so speed, reuse, and compliance are inherited by default
- Shape an operating model that balances enterprise standards with speed and ownership
Scale the AI platform
Lead the reusable platform that lets teams build and operate AI securely, reliably, and repeatedly. The point is impact, not infrastructure for its own sake, so each new capability is faster, safer, and less expensive to deliver than the one before.
- Agentic foundations, orchestration, retrieval and knowledge access, and model selection
- Evaluation, observability, and integration with enterprise data and services
- The AI Development Lifecycle (AIDLC), the paved path that builds in standards, tests, and security from the start, taking project setup from days to minutes and passing quality gates on the first pull request
Transform the benefits experience
Lead the delivery of agentic, AI\-powered experiences that reimagine how participants understand and act on their benefits, and set a high bar for usefulness, simplicity, accuracy, and trust.
- Move from answering questions to taking action on a participant's behalf, with the right human oversight
- Own the full outcome, from shipping through adoption, reliability, and experience
- Hold teams to measurable value in production, at enterprise\-grade reliability
Reimagine work through intelligent automation
Find and scale the opportunities where AI removes friction, augments human judgment, and transforms complex operational processes.
- Advance automation from rules\-based, to AI\-assisted, to agentic
- Move beyond scripts and isolated tools toward adaptive workflows that connect knowledge, decisions, and action
- Industrialize automation at volume while preserving appropriate human oversight
Make trust a product capability
Build responsible AI into how solutions are designed, evaluated, released, monitored, and improved. Partner with risk, security, privacy, legal, and compliance leaders to create controls rigorous enough for a high\-trust environment and practical enough to support speed. At Alight, governance operates as an enablement function that weighs risk alongside platform, architecture, cost, and strategy, rather than as a separate compliance exercise.
Build the organization
Recruit, develop, and lead a world\-class AI organization spanning platform engineering, applied AI, product delivery, intelligent automation, quality and evaluation, and responsible AI. Create an environment where strong leaders have real ownership, exceptional technical talent does the best work of their careers, and teams are measured by outcomes.
Represent Alight's AI ambition
Serve as a credible and compelling voice on AI with clients, partners, executive leaders, and the broader market. Listen closely to the problems clients are working to solve, translate those needs into strategic choices, and explain Alight's direction with clarity and substance.
The Leader We Are Looking For
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You are a proven technology and AI leader who has built real systems, led significant organizations, and operated with accountability for business outcomes. Your background may be multidisciplinary, and what matters to us is what you have built, the scale at which it operated, and the decisions you personally owned.
The strongest candidates will bring many of the following:
- Led a multi\-team AI, machine learning, software, or platform organization through other senior leaders
- Deployed AI or complex technology products into production for a large user population, with measurable value
- Current fluency in generative AI, large language models, agentic systems, retrieval, evaluation, and production AI engineering
- Built shared platforms or foundational capabilities that multiple product and engineering teams depend on
- Owned a meaningful investment portfolio or budget, and made clear build, buy, and partner decisions without becoming captive to any single vendor
- Operated in a regulated, high\-trust environment, with a practical command of AI risk, privacy, security, and lifecycle governance
- Recruited and developed senior technical leaders, and communicated with equal ease across engineers, clients, and executives
Technical depth is essential. You can challenge an architecture, probe an evaluation approach, and tell a production\-ready system from one that only looks it. That judgment is what earns the trust of the engineers and leaders you will lead, and what lets you set a bar the whole organization rises to.
Application and Interview
By applying for a position with Alight, you understand that, should you be made an offer, it will be contingent on your undergoing and successfully completing a background check consistent with Alight’s employment policies. Background checks may include some or all the following based on the nature of the position: SSN/SIN validation, education verification, employment verification, and criminal check, search against global sanctions and government watch lists, credit check, and/or drug test. You will be notified during the hiring process which checks are required by the position.
Alight requires all virtual interviews to be conducted on video. Please be aware that Alight is a camera\-on culture and may require occasional travel to one of our physical office locations.
Our commitment to Inclusion
We celebrate differences and believe in fostering an environment where everyone feels valued, respected, and supported. We know that diverse teams are stronger, more innovative, and more successful.
At Alight, we welcome and embrace all individuals, regardless of their background, and are dedicated to creating a culture that enables every employee to thrive. Join us in building a brighter, more inclusive future.
As part of this commitment, Alight will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact [email protected].
Equal Opportunity Policy Statement
Alight is an Equal Employment Opportunity employer and does not discriminate against anyone based on sex, race, color, religion, creed, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, marital or domestic partner status, citizenship, military or veteran status, sexual orientation, gender, gender identity or expression, genetic information, or any other legally protected characteristics or conduct covered by federal, state, or local law. In addition, we take affirmative action to employ disabled persons, disabled veterans, and other covered veterans.
Alight provides reasonable accommodations to the known limitations of otherwise qualified employees and applicants for employment with disabilities and sincerely held religious beliefs, practices and observances, unless doing so would result in undue hardship. Applicants for employment may request reasonable accommodations/modifications by contacting their recruiter.
Authorization to work in the Employing Country
Applicants for employment in the country in which they are applying (Employing Country) must have work authorization that does not, now or in the future, require sponsorship of a visa for employment authorization in the Employing Country and with Alight.
Note, this job description does not restrict management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units.
\#LI\-Remote
We offer you a competitive total rewards package, continuing education \& training, and tremendous potential with a growing worldwide organization.
Salary Pay Range
Minimum :
265,000\.00 USD
Maximum :
290,000\.00 USD
Pay Transparency Statement: Alight considers a variety of factors in determining whether to extend an offer of employment and in setting the appropriate compensation level, including, but not limited to, a candidate’s experience, education, certification/credentials, market data, internal equity, and geography. Alight makes these decisions on an individualized, non\-discriminatory basis. Bonus and/or incentive eligibility are determined by role and level. Alight also offers a comprehensive benefits package; for specific details on our benefits package, please visit: Wellbeing and Benefits Selector Page \- Alight
DISCLAIMER:
Nothing in this job description restricts management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units.
Alight Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, creed, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, pregnancy, childbirth or related medical condition, veteran, marital, parental, citizenship, or domestic partner status, or any other status protected by applicable national, federal, state or local law. Alight Solutions is committed to a diverse workforce and is an affirmative action employer.
Salary Context
This $265K-$290K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Alight Solutions, 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 in Demand for This Role
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 $214,900 based on 6,420 positions with disclosed compensation. This role's midpoint ($277K) sits 29% above the category median. Disclosed range: $265K to $290K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Alight Solutions AI Hiring
Alight Solutions has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Deerfield, IL, US. Compensation range: $220K - $290K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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