Interested in this AI/ML Engineer role at Travelers?
Apply Now →About This Role
Who Are We?
Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.
Compensation Overview
The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance\-based cash incentive awards.
Salary Range
$120,400\.00 \- $198,700\.00Target Openings
1What Is the Opportunity?
What is the Opportunity?
As a member of Enterprise AI and Emerging Technologies, you’ll be joining a strategic and collaborative team that is passionate about transforming our business and technology capabilities and paving the way for best\-in\-class technology.
As Director, Product Owner – Enterprise AI Assistants, you'll lead a dynamic team, balancing strategic product leadership with hands\-on stakeholder engagement and delivery. This role requires guiding teams through complex AI capability rollouts while actively shaping the roadmap and priorities for enterprise\-wide AI Assistant platforms. In this highly visible role, we will look to you to:
- Own and evolve the product strategy and roadmap for AI Assistants, ensuring alignment with enterprise AI goals and business priorities.
- Define and maintain a prioritized, execution\-ready backlog that drives measurable outcomes for approximately 30,000 enterprise users.
- Play a key role in growing and transforming enterprise AI adoption through structured capability enablement, stakeholder socialization, and continuous delivery.
- Lead a highly effective and collaborative team in supporting a portfolio of AI Assistant tools.
Applicants must be authorized to work for ANY employer in the US. The company does not sponsor/support H\-1B petitions, TN, or Forms I\-983/STEM OPT, this this role.What Will You Do?
- Lead and develop the AI Assistants Team driving enterprise AI Assistant adoption across Travelers.
- Define, prioritize, and maintain a comprehensive product backlog for AI Assistants ensuring execution\-ready work aligned to business outcomes.
- Maintain hands\-on involvement in product decisions, backlog refinement, acceptance criteria, and the delivery of AI capabilities across the enterprise.
- Partner with stakeholders across business lines, Legal, Governance, and Gen AI leads to ensure AI Assistant roadmaps align with enterprise strategy and compliance requirements.
- Contribute to product standards and best practices for AI capability enablement, feature rollout, and performance monitoring across teams.
- Troubleshoot and resolve critical product and delivery issues, leading response efforts when adoption, compliance, or platform challenges arise.
- Champion the use of enterprise AI Assistants across the organization through education, stakeholder socialization, and active advocacy.
What Will Our Ideal Candidate Have?
- Bachelor’s degree.
- Two years of experience in Agile product management.
- Two years of work experience within the discipline being supported (e.g.: Claim, Risk Control, Technology, Project Management, Production, Application Development, etc.).
- Three years of experience articulating and translating business strategy, product vision, and analysis for a product.
- Agile Mindset: Embody Agile core values of openness, courage, respect, focus, and commitment.
- Infuse Agile principles, practices and methodologies to achieve team success.
- Product Mindset: Focus on defining a product value proposition that aligns with and supports the circle/value stream objectives and which is the north star for the team.
- Influence: Ability to influence behaviors of leaders at all levels and without traditional hierarchy.
- Servant Leadership: Foster an environment where individuals thrive as empowered and equal members of a team.
- Communication: Ability to communicate thoughts, concepts, practices effectively at all levels, adjusting as needed to a target audience.
- Collaboration: Expertise working with others in a cross\-functional multi\-team environment.
- Continuous Improvement: Demonstrate a commitment to continually improve, share learning with others and encourage team development.
What is a Must Have?
- Three years of work experience in related field.
- Three years of experience motivating/influencing teams.
What Is in It for You?
- Health Insurance: Employees and their eligible family members – including spouses, domestic partners, and children – are eligible for coverage from the first day of employment.
- Retirement: Travelers matches your 401(k) contributions dollar\-for\-dollar up to your first 5% of eligible pay, subject to an annual maximum. If you have student loan debt, you can enroll in the Paying it Forward Savings Program. When you make a payment toward your student loan, Travelers will make an annual contribution into your 401(k) account. You are also eligible for a Pension Plan that is 100% funded by Travelers.
- Paid Time Off: Start your career at Travelers with a minimum of 20 days Paid Time Off annually, plus nine paid company Holidays.
- Wellness Program: The Travelers wellness program is comprised of tools, discounts and resources that empower you to achieve your wellness goals and caregiving needs. In addition, our mental health program provides access to free professional counseling services, health coaching and other resources to support your daily life needs.
- Volunteer Encouragement: We have a deep commitment to the communities we serve and encourage our employees to get involved. Travelers has a Matching Gift and Volunteer Rewards program that enables you to give back to the charity of your choice.
Employment Practices
Travelers is an equal opportunity employer. We value the unique abilities and talents each individual brings to our organization and recognize that we benefit in numerous ways from our differences.
In accordance with local law, candidates seeking employment in Colorado are not required to disclose dates of attendance at or graduation from educational institutions.
If you are a candidate and have specific questions regarding the physical requirements of this role, please send us an email so we may assist you.
Travelers reserves the right to fill this position at a level above or below the level included in this posting.
To learn more about our comprehensive benefit programs please visit http://careers.travelers.com/life\-at\-travelers/benefits/.
Salary Context
This $120K-$198K range is below the median 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 Travelers, 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. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($159K) sits 26% below the category median. Disclosed range: $120K to $198K.
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.
Travelers AI Hiring
Travelers has 5 open AI roles right now. They're hiring across AI Agent Developer, AI Software Engineer, AI/ML Engineer, Data Engineer. Positions span Atlanta, GA, US, Hartford, CT, US. Compensation range: $198K - $230K.
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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