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Job Description
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DIRECTOR OF AGENTIC AUTOMATION
Owns the Distribution \& Placement engineering group
About Acrisure
Acrisure is a global fintech leader empowering ambitious businesses and individuals with customized solutions that drive growth and impact. We combine cutting\-edge technology with expert human support to deliver tailored insurance, reinsurance, payroll, benefits, cybersecurity, mortgage services, and more.
In the last twelve years, Acrisure has grown from $38 million in revenue to nearly $5 billion and now employs more than 19,000 colleagues across 20\+ countries. Built on entrepreneurial spirit, we prioritize leadership, accountability, and collaboration — equipping our teams to work at the highest levels and solve meaningful challenges.
ROLE OVERVIEW
The Director of Agentic Automation owns engineering for Distribution and Placement — the systems and agentic workflows that move submissions to market and quotes back to producers. The domain spans the placement layer above the AMSs, agentic application\-to\-bind, and the producer\-facing submission and placement experience.
This is a senior leadership role that pairs deep insurance\-domain judgement with a clear vision for where AI and agentic automation transform distribution. The Director owns the domain's outcomes end to end: its product direction, its roadmap, its delivery, and its relationship with the business. They lead a group of pods — each with a Tech Lead and engineers who own deep technical design and build — and are accountable for translating business need into systems that measurably move how the business places and binds risk. They set strategy and direction; their pod leads own the architecture and the code.
STRATEGIC OWNERSHIP
- Own the Distribution and Placement domain end to end — its product strategy, roadmap, delivery outcomes, and the business relationships that depend on it.
- Set the vision for where agentic automation reshapes distribution and placement, and turn it into a concrete, sequenced roadmap the business can fund and the team can build.
- Own the three\-way relationship with the business\-side P\&L owner and the Delivery Lead — bringing the domain and product reality (what's worth building, what it's worth, what it unlocks) to the prioritisation conversation.
- Lead, grow, and develop the group's pods — currently two, scaling as the domain's scope is confirmed — holding the bar on talent and ensuring the Tech Leads own technical direction within their pods.
- Engage directly with the C\-suite, carriers, producers, and senior business stakeholders; commit to outcomes and deliver them.
KEY RESPONSIBILITIES
- Own the strategy and roadmap for Distribution and Placement systems (Sureplace, Leftseat, and the agentic placement/submission flow), and be accountable for their business outcomes.
- Lead the domain's pods, partnering with Tech Leads who own architecture, technical direction, and delivery quality within each pod.
- Shape new initiatives before they enter build — defining scope, success metrics, and the execution approach — so the team builds the right thing.
- Bring deep insurance\-domain judgement to product and prioritisation decisions; push back intelligently and hold the line credibly with the business.
- Partner with the Delivery Lead and P\&L owner to prioritise the portfolio and protect the team's focus.
- Diagnose delivery and product issues across technical, organisational, and process dimensions, and move decisively to resolve them.
- Stay technically fluent enough to engage credibly with engineers, evaluate trade\-offs, and make sound calls quickly — without owning the codebase yourself.
- Engage at senior levels across the organisation to unblock the domain and represent it to the business and external partners.
WHAT SUCCESS LOOKS LIKE
- Distribution and Placement systems are demonstrably moving the business's placement and bind metrics — producers decide faster, more submissions reach market, more business binds.
- The agentic\-automation roadmap is real and delivering: shipped capability, not slideware.
- The roadmap is delivered on outcomes, with the business confident in what's being built and why.
- The pods are high\-performing and growing, with strong Tech Leads owning the technical core.
- The business treats the Director as a trusted partner on where technology takes distribution next.
- The Senior Director of Engineering has high confidence in delivery and direction across the domain.
EXPERIENCE REQUIRED
- 15\+ years building data\- and technology\-driven products, with significant leadership in insurance or other complex, regulated industries.
- Deep insurance\-domain fluency — underwriting, distribution, placement, MGA/program development, or adjacent — sufficient to own product direction and hold the line with the business.
- Proven track record translating AI, data, and automation capabilities into real products and measurable business outcomes.
- Experience owning a domain, product line, or business end to end, accountable for its strategy and outcomes over time.
- Demonstrated ability to build and lead teams, including standing up capability from scratch and growing high\-performing groups.
- Strong technical fluency: able to engage credibly with engineers, reason about architecture and trade\-offs, and direct technical teams — while relying on Tech Leads to own deep design and build.
- Demonstrated ability to influence senior stakeholders, including C\-suite, carriers, and enterprise partners.
- Comfort operating in ambiguity and high\-pressure environments, with a bias to decisive action.
- Founder, GM, or P\&L experience a strong plus; hands\-on experience building with modern AI/agentic tooling highly desirable.
Candidates should be comfortable with an on\-site presence to support collaboration, team leadership, and cross\-functional partnership.
Benefits and Perks:
- Competitive compensation
- Generous vacation policy, paid holidays, and paid sick time
- Medical Insurance, Dental Insurance, and Vision Insurance (employee\-paid)
- Company\-paid Short\-Term and Long\-Term Disability Insurance
- Company\-paid Group Life insurance
- Company\-paid Employee Assistance Program (EAP) and Calm App subscription
- Employee\-paid Pet Insurance and optional supplemental insurance coverage
- Vested 401(k) with company match and financial wellness programs
- Flexible Spending Account (FSA), Health Savings Account (HSA) and commuter benefits options
- Paid maternity leave, paid paternity leave, and fertility benefits
- Career growth and learning opportunities
- …and so much more!
Please note: This list is not reflective of all benefits. Enrollment waiting periods or eligibility criteria may apply to certain benefits. Offerings may vary based on subsidiary entity or geographic location.
Making a lasting impact on the communities it serves, Acrisure has pledged more than $22 million through its partnerships with Corewell Health Helen DeVos Children's Hospital in Grand Rapids, Michigan, UPMC Children's Hospital in Pittsburgh, Pennsylvania and Blythedale Children's Hospital in Valhalla, New York.
Acrisure is an Equal Opportunity Employer.
At Acrisure, we firmly believe that an inclusive workforce drives innovation, creativity, and ultimately, our collective success.
We recruit, hire, employ, train, promote, and compensate individuals based on job\-related qualifications and abilities. Acrisure also has a longstanding policy of providing a work environment that respects the dignity and worth of each individual and is free from all forms of employment discrimination.
Acrisure also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief, in accordance with applicable laws. If you need to inquire about an accommodation, or need assistance with completing the application process, please email [email protected].
California residentscan learn more about our privacy practices for applicants by visiting the Acrisure California Applicant Privacy Policy available at www.Acrisure.com/privacy/caapplicant.
Final candidates will be required to complete post\-offer verification processes related to the role and in accordance with applicable laws.
Recruitment Fraud:Please visit here to learn more about our Recruitment Fraud Notice.
Welcome, your new opportunity awaits you.
There are amazing opportunities for talented people in every part of our business. We invite you to find your next great opportunity with us.
Executive Search Firms \& Staffing Agencies
To Executive Search Firms \& Staffing Agencies: Acrisure does not accept unsolicited resumes from any agencies that have not signed a mutual service agreement. All unsolicited resumes will be considered Acrisure's property, and Acrisure will not be obligated to pay a referral fee. This includes resumes submitted directly to Hiring Managers without contacting Acrisure's Human Resources Talent Department.
\#LI\-onsite
\#BI\-onsite
Pay Details:
The base compensation range for this position is $245,000 \- $287,000\. This range reflects Acrisure's good faith estimate at the time of this posting. Placement within the range will be based on a variety of factors, including but not limited to skills, experience, qualifications, location, and internal equity.Candidates should be comfortable with an on\-site presence to support collaboration, team leadership, and cross\-functional partnership.
Why Join Us:
At Acrisure, we’re building more than a business, we’re building a community where people can grow, thrive, and make an impact. Our benefits are designed to support every dimension of your life, from your health and finances to your family and future.
Making a lasting impact on the communities it serves, Acrisure has pledged more than $22 million through its partnerships with Corewell Health Helen DeVos Children's Hospital in Grand Rapids, Michigan, UPMC Children's Hospital in Pittsburgh, Pennsylvania and Blythedale Children's Hospital in Valhalla, New York.
Employee Benefits
We also offer our employees a comprehensive suite of benefits and perks, including:
- Physical Wellness: Comprehensive medical insurance, dental insurance, and vision insurance; life and disability insurance; fertility benefits; wellness resources; and paid sick time.
- Mental Wellness: Generous paid time off and holidays; Employee Assistance Program (EAP); and a complimentary Calm app subscription.
- Financial Wellness: Immediate vesting in a 401(k) plan; Health Savings Account (HSA) and Flexible Spending Account (FSA) options; commuter benefits; and employee discount programs.
- Family Care: Paid maternity leave and paid paternity leave (including for adoptive parents); legal plan options; and pet insurance coverage.
- … and so much more!
*This list is not exhaustive of all available benefits. Eligibility and waiting periods may apply to certain offerings. Benefits may vary based on subsidiary entity and geographic location.*
Acrisure is an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, religion, sex, national origin, disability, or protected veteran status. Applicants may request reasonable accommodation by contacting *[email protected]*.
Final candidates will be required to complete post\-offer verification processes related to the role and in accordance with applicable laws.
California Residents: Learn more about our privacy practices for applicants by visiting the Acrisure California Applicant Privacy Policy.
Recruitment Fraud: Please visit here to learn more about our Recruitment Fraud Notice.
Welcome, your new opportunity awaits you.
Salary Context
This $245K-$287K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Acrisure LLC, 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 $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($266K) sits 22% above the category median. Disclosed range: $245K to $287K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Acrisure LLC AI Hiring
Acrisure LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $287K - $287K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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