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Job Description:
AXA XL is an Equal Opportunity Employer.
Head of Technology \& AI, Americas and Chief Client Office
Locations: US
AXA XL’s Head of Technology \& AI, Americas and Chief Client Office is a key senior executive, leadership team role in the Technology \& AI function, accountable for acting as the strategic technology and AI partner to deliver for the Americas and the Chief Client Office leadership teams, in cooperation with the Tech \& AI organization.
The role ensures business strategy is translated into a coherent technology and AI roadmaps, aligning investment, engineering capacity, operating model change, and measurable outcomes. This leader shapes demand, challenges priorities, drives decision\-making, and ensures delivery accountability within the Technology \& AI function for the Americas and the Chief Client Office.
Operating as a trusted executive partner, balancing innovation with value, risk, regulatory requirements, and operational resilience, this role reports to AXA XL’s Chief Technology \& AI Officer with a dotted line to the Chief Executive Officer, Americas.Whatyou’ll be doing
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Executive Technology \& AI Leadership* Act as the primary technology and AI partner to the Americas and the Chief Client Office shaping business direction through technology\-led opportunities.
- Provide insights on AI disruption, competitor landscape, and modern digital and AI business models relevant to insurance.
- Translate complex technology concepts into commercial and operational implications for executive decision\-making.
Strategy\-to\-Execution Translation* Convert business strategy into a prioritized and funded technology and AI roadmap.
- Define the sequencing of initiatives based on value, feasibility, regulatory constraints, and delivery capacity.
- Ensure roadmaps integrate digital, data, AI, automation, and core platform modernization.
- Drive robust partnerships within the Tech \& AI leadership team to ensure common principles, frameworks and guidelines are deployed and executed with effective coordination across all disciplines in the function.
Enterprise Alignment \& Investment Governance* Represent the Americas and the Client Office into enterprise technology investment forums.
- Own business unit\-level investment cases, ensuring clarity of ROI, outcomes, and measurable benefits.
- Challenge the business on value definition and ensure initiatives meet enterprise architecture, security, and AI governance requirements.
Portfolio Ownership \& Delivery Oversight* Own the technology and AI portfolio for the Americas and the Client Office, ensuring delivery performance, dependencies, and risks are actively managed.
- Hold delivery teams accountable for execution outcomes while ensuring the business fulfils its accountabilities (SMEs, process change, adoption).
- Provide clear reporting to Global Leadership Team partner(s) on delivery confidence, risks, financial position, and benefits tracking.
Stakeholder Management \& Executive Influence* Challenging and influencing senior stakeholders with poise and composure, facilitating decision\-making forums, resolving prioritization conflicts and driving outcomes.
- Build alignment across business functions including underwriting, claims, pricing, finance, customer operations, and distribution.
AI Adoption \& Business Transformation* Drive enterprise AI adoption within the business unit, ensuring:
- + high\-value use cases are identified
+ adoption and operating model impacts are planned
+ workforce readiness is supported
+ human\-in\-the\-loop and control frameworks are implemented
- Ensure AI is embedded into workflows rather than delivered as standalone tools.
Risk, Resilience \& Regulatory Partnership* Partner with Risk, Compliance, Legal, and Security to ensure delivery aligns to regulatory and control requirements.
- Ensure AI initiatives comply with Responsible AI, privacy, and model risk expectations.
- Ensure technology resilience and service continuity risks are visible and actively managed.
Commercial and Vendor Leadership* Partner with Procurement and Technology leadership to shape vendor strategy aligned to business unit priorities.
- Support contract negotiations, supplier performance management, and strategic partnerships.
- Ensure commercial outcomes align to delivery outcomes and service performance.
Whatyou’ll bring
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We’re looking for someone who has these abilities and skills:
Commercial Acumen* Keen understanding of business strategy, financial drivers, and operational performance levers.
- Able to challenge executives constructively and influence investment decisions.
Technology \& AI Leadership* Keen understanding of enterprise technology including:
- + product engineering and agile delivery
+ cloud platforms and modern architecture
+ data platforms and AI enablement
+ automation and workflow transformation
- Outstanding ability to evaluate AI opportunities pragmatically (value, feasibility, risk).
Delivery \& Portfolio Discipline* Excellent portfolio and program oversight capability.
- Ability to balance competing priorities, resource constraints, and dependencies.
- Robust governance, reporting, and delivery confidence management.
Risk \& Regulatory Mindset (Insurance Context)* Keen understanding of regulated environments and technology control frameworks.
- Awareness of Responsible AI, data privacy, and model risk management principles.
Relationship Management \& Leadership* Ability to build deep trust across business and technology.
- Excellent conflict resolution skills and ability to drive alignment across competing agendas.
Whatweoffer
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Inclusion
AXA XL is committed to equal employment opportunity and will consider applicants regardless of gender, sexual orientation, age, ethnicity and origins, marital status, religion, disability, or any other protected characteristic. At AXA XL, we know that an inclusive culture enables business growth and is critical to our success. That’s why we have made a strategic commitment to attract, develop, advance and retain the most inclusive workforce possible, and create a culture where everyone can bring their full selves to work and reach their highest potential. *It’s about helping one another — and our business — to move forward and succeed.*
- Five Business Resource Groups focused on gender, LGBTQ\+, ethnicity and origins, disability and inclusion with 20 Chapters around the globe.
- Robust support for Flexible Working Arrangements
- Enhanced family\-friendly leave benefits
- Named to the Diversity Best Practices Index
- Signatory to the UK Women in Finance Charter
Learn more at axaxl.com/about\-us/inclusion\-and\-diversity. AXA XL is an Equal Opportunity Employer. Total Rewards
AXA XL’s Reward program is designed to take care of what matters most to you, covering the full picture of your health, wellbeing, lifestyle and financial security. It provides competitive compensation and personalized, inclusive benefits that evolve as you do.
We’re committed to rewarding your contribution for the long term, so you can be your best self today and look forward to the future with confidence. Sustainability
At AXA XL, Sustainability is integral to our business strategy. In an ever\-changing world, AXA XL protects what matters most for our clients and communities. We know that sustainability is at the root of a more resilient future. Our 2023\-26 Sustainability strategy, called “Roots of resilience”, focuses on protecting natural ecosystems, addressing climate change, and embedding sustainable practices across our operations.
Our Pillars:* Valuing nature: How we impact nature affects how nature impacts us. Resilient ecosystems \- the foundation of a sustainable planet and society – are essential to our future. We’re committed to protecting and restoring nature – from mangrove forests to the bees in our backyard – by increasing biodiversity awareness and inspiring clients and colleagues to put nature at the heart of their plans.
- Addressing climate change: The effects of a changing climate are far\-reaching and significant. Unpredictable weather, increasing temperatures, and rising sea levels cause both social inequalities and environmental disruption. We're building a net zero strategy, developing insurance products and services, and mobilizing to advance thought leadership and investment in societal\-led solutions.
- Integrating ESG: All companies have a role to play in building a more resilient future. Incorporating ESG considerations into our internal processes and practices builds resilience from the roots of our business. We are training our colleagues, engaging our external partners, and evolving our sustainability governance and reporting.
- AXA Hearts in Action: We have established volunteering and charitable giving programs to help colleagues support causes that matter most to them, known as AXA XL’s “Hearts in Action” programs. These include our Matching Gifts program, Volunteering Leave, and our annual volunteering day – the Global Day of Giving.
For more information, please see axaxl.com/sustainability.
The U.S. base salary range for this position is $210,000 to $250,000 USD.
Actual pay will be determined based upon the individual’s skills, experience and location. We strive for market alignment and internal equity with our colleagues’ pay.
At AXA XL, we know how important physical, mental, and financial health are to our employees, which is why we are proud to offer benefits such as a competitive retirement savings plan, health and wellness programs, and many other benefits. We also believe in fostering our colleagues' development and offer a wide range of learning opportunities for colleagues to hone their professional skills and to position themselves for the next step of their careers.Whoweare
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AXA XL, the P\&C and specialty risk division of AXA, is known for solving complex risks. For mid\-sized companies, multinationals and even some inspirational individuals we don’t just provide re/insurance, we reinvent it.
How? By combining a comprehensive and efficient capital platform, data\-driven insights, leading technology, and the best talent in an agile and inclusive workspace, empowered to deliver top client service across all our lines of business property, casualty, professional, financial lines and specialty.
With an innovative and flexible approach to risk solutions, we partner with those who move the world forward.
Learn more at axaxl.com
Salary Context
This $210K-$250K 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 AXA, 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. C-Level-level AI roles across all categories have a median of $250,000. This role's midpoint ($230K) sits 7% above the category median. Disclosed range: $210K to $250K.
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.
AXA AI Hiring
AXA has 3 open AI roles right now. They're hiring across AI/ML Engineer, AI Architect. Positions span New York, NY, US, Hartford, CT, US. Compensation range: $222K - $250K.
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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