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About This Role
$200,000 \- $300,000 Total Compensation
Our fast\-paced and collaborative environment inspires us to create, think, and challenge each other in ways that make our solutions and our teams better. Whether you’re interested in engineering or development, marketing or sales, or something else – if this sounds like you, then we’d love to hear from you!
We are headquartered in Denver, Colorado, with offices in the US, Canada, and India.
$200,000 \- $300,000 Total Compensation
About the Role
Vertafore's AI organization is moving fast — from agentic workflows to intelligent document processing and predictive analytics. These systems are in production, serving thousands of agencies and carriers across North America, and the bar for reliability, scalability, and craft is high.
We're looking for an AI Engineering Leader who leads from the front. You'll own delivery for one of our core AI product domains, managing a small team of engineers while staying close enough to the work that you're the person your team turns to when the architecture gets hard. You’ll be a hands on leader with expertise in designing, evaluating, and shipping AI based features.
This is not a role for someone who has stepped fully away from the code. You are an active participant in the team, reviewing PR’s, making technical decisions, and writing code. Your value multiplier is the team you build and enable, but your credibility comes from the depth you bring.
What You'll Do
Lead a High\-Performing AI Engineering Team
- Manage, mentor, and grow a team of 4–8 engineers. Running 1:1s, setting technical direction, and creating clear paths for individual development
- Foster a culture of rigor, fast iteration, and creative problem solving. Build a team where engineers are empowered to raise problems early and move from experiment to production without unnecessary friction
- Partner with recruiting to hire strong AI engineering talent and retain it through meaningful work and clear growth
Own Technical Delivery for Your Domain
- Drive the end\-to\-end delivery of AI features and systems within your team's scope, from design to deployment to post\-production observability
- Be the accountable technical voice for your domain: scope estimates, architectural decisions, tradeoff documentation, and post\-mortems all run through you
- Work closely with a product manager to translate customer problems and business priorities into a well\-sequenced engineering roadmap
Stay Hands\-On at the Right Level
- Contribute meaningfully to system design, code reviews, and debugging when it matters with a focus on greenfield work, critical path systems, or when the team is blocked
- Set and uphold engineering standards for your team: testing strategy, evaluation frameworks, model observability, and responsible deployment practices
- Know when to write the code yourself and when your highest\-leverage move is unblocking someone else
Build and Operate Production AI Systems
- Oversee the design and operation of LLM\-powered features, ETL pipelines, agentic workflows, and/or document extraction systems
- Maintain a high bar for production quality: latency, cost, reliability, and behavioral consistency across a diverse multi\-tenant customer base
- Build feedback loops and monitoring that detect model drift, degraded outputs, and edge case failures before customers do
Collaborate Across the Organization
- Work with peer engineering teams, platform engineering, and data engineering to share infrastructure, avoid duplication, and raise the AI platform's overall capability
- Communicate clearly to surface risks early, quantify tradeoffs, and clear a path to rapid development and iteration for you team
- Occasionally engage directly with customers, customer success, or implementation teams to ground your team's work in real\-world usage patterns
Required Qualifications
- 5\+ years of experience in machine learning, AI engineering, or applied data science
- 1–3\+ years of direct people management or formal tech lead experience with responsibility for team delivery
- Hands\-on production experience with one or more of: LLM\-powered applications, agentic workflows, document extraction pipelines, or classical ML systems
- Proficiency in Python and familiarity with the modern AI engineering stack — LangChain/LangGraph (or equivalent), vector databases, prompt engineering, and model evaluation tooling
- Experience deploying and operating AI systems in a cloud environment (AWS preferred)
- Strong written and verbal communication skills — able to write a crisp design doc, run a productive design review, and give clear status to non\-technical stakeholders
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field
Preferred Qualifications
- Experience in B2B SaaS, insurance, financial services, or another regulated vertical
- Familiarity with MLOps tooling
- Exposure to intelligent document processing, for example parsing PDFs, structured tables, or semi\-structured data at scale
- Experience with LLM observability and AI gateway tooling (e.g., LangSmith, Helicone, Portkey, LiteLLM)
- Background building systems with human\-in\-the\-loop workflows and agentic task orchestration
Why This Role
You'll have real ownership — of a team, of a technical domain, and of shipped product used by insurance professionals across North America. You'll have leadership who is fully committed to delivering real AI value to customers and invest in your growth. And you'll be operating in an industry that is genuinely early in its AI transformation, with the data, infrastructure, and customer relationships already in place to make the work matter.
Why Vertafore is the place for you: \*Canada Only
- The opportunity to work in a space where modern technology meets a stable and vital industry
- Medical, vision \& dental plans
- Life, AD\&D
- Short Term and Long Term Disability
- Pension Plan \& Employer Match
- Maternity, Paternity and Parental Leave
- Employee and Family Assistance Program (EFAP)
- Education Assistance
- Additional programs \- Employee Referral and Internal Recognition
Why Vertafore is the place for you: \*US Only
- The opportunity to work in a space where modern technology meets a stable and vital industry
- We have a Flexible First work environment! Our North America team members use our offices for collaboration, community and team\-building, with members asked to sometimes come into an office and/or travel depending on job responsibilities. Other times, our teams work from home or a similar environment.
- Medical, vision \& dental plans
+ PPO \& high\-deductible options
- Health Savings Account \& Flexible Spending Accounts Options:
+ Health Care FSA
+ Dental \& Vision FSA
+ Dependent Care FSA
+ Commuter FSA
- Life, AD\&D (Basic \& Supplemental), and Disability
- 401(k) Retirement Savings Plain \& Employer Match
- Supplemental Plans \- Pet insurance, Hospital Indemnity, and Accident Insurance
- Parental Leave \& Adoption Assistance
- Employee Assistance Program (EAP)
- Education \& Legal Assistance
- Additional programs \- Tuition Reimbursement, Employee Referral, Internal Recognition, and Wellness
- Commuter Benefits (Denver)
The selected candidate must be legally authorized to work in the United States.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all the job responsibilities, duties, skill, or working conditions. In addition, this document does not create an employment contract, implied or otherwise, other than an "at will" relationship.
Vertafore strongly supports equal employment opportunity for all applicants regardless of race, color, religion, sex, gender identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, sexual orientation, genetic information, or any other characteristic protected by state or federal law.
The Professional Services (PS) and Customer Success (CX) bonus plans are a quarterly monetary bonus plan based upon individual and practice performance against specific business metrics. Eligibility is determined by several factors including: start date, good standing in the company, and actives status at time of payout.
The Vertafore Incentive Plan (VIP) is an annual monetary bonus for eligible employees based on both individual and company performance. Eligibility is determined by several factors including: start date, good standing in the company, and actives status at time of payout.
Commission plans are tailored to each sales role but common components include quota, MBO's and ABPMs. Salespeople receive their formal compensation plan within 30 days of hire.
*Vertafore is a drug free workplace and conducts preemployment drug and background screenings.*
*We do not accept resumes from agencies, headhunters or other suppliers who have not signed a formal agreement with us.*
*We want to make sure our recruiting process is accessible for everyone. if you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact* *[email protected]*
*Just a note, this contact information is for accommodation requests only.*
Additional Requirements and Details:
- Travel required up to 10% of the time.
- Located and working from an office location.
- Occasional lifting and/or moving up to 10 pounds.
- Frequent repetitive hand and arm movements required to operate a computer.
- Specific vision abilities required by this job include close vision (working on a computer, etc.).
- Frequent sitting and/or standing.
THE VERTAFORE STORY
Over the past 50 years, Vertafore has advanced the entire insurance distribution channel with the best software solutions in the industry. Today, we’re proud to say hundreds of thousands of Vertafore users rely on our solutions to write business faster, reduce costs, and fuel growth by increasing collaboration and streamlining processes. Vertafore leads the industry with secure, cloud\-based mobile products that provide superior reporting and analytics, delivering actionable insight— right when customers need it most. We partner with other leading technology companies to deliver comprehensive solutions to improve the way our customers do business and serve their customers.
The Vertafore Way
Insurance is about relationships, and technology should make those relationships stronger. That’s why, at Vertafore, it’s our mission to transform the way the industry operates by putting people at the heart of insurance technology. By focusing on our customers, becoming better every day, and delivering results you can see, we provide the level of trust and security that insurance is all about.
- Bias to Action: We're united by an innate drive to take action and make a difference in the technology and insurance spaces.
- Win Together: We work together as one team, showing empathy and respect along the way.
- Show Up Curious: We work to challenge one another to push boundaries and think beyond the box.
- Say It, Do It: We honor every one of our commitments because integrity is important to us.
- Customer Success is Our Success: We cultivate authentic relationships and follow up by actively listening to their needs.
- We Love Insurance: We appreciate the impact insurance has on the world.
Is this role not an exact fit for you? Keep an eye on our Careers Page for other positions!
*Vertafore is a drug free workplace and conducts preemployment drug and background screenings**.*
*The selected candidate must be legally authorized to work in the United States.*
*The above statements are intended to describe the general nature and level of work being* *performed by people assigned to this job. They are not intended to be an exhaustive list of all the job responsibilities, duties, skill, or working conditions. In addition, this document does not create an employment contract, implied or otherwise, other than an "at will" relationship.*
*Vertafore strongly supports equal employment opportunity for all applicants regardless of race, color, religion, sex, gender identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, sexual orientation, genetic information, or any other characteristic protected by state or federal law.*
*We do not accept resumes from agencies, headhunters, or other suppliers who have not signed a formal agreement with us.*
Vertafore is a Flexible First working environment which allows team members to work from home as often as you’d like, while using our offices as a place for collaboration, community, and teambuilding. There are times you may be asked to come into an office and/or travel for specific meetings for a specific business purpose and this varies by job responsibilities.
Salary Context
This $200K-$300K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Vertafore, 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 $178,940 based on 11,900 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($250K) sits 40% above the category median. Disclosed range: $200K to $300K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Vertafore AI Hiring
Vertafore has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $160K - $300K.
Location Context
AI roles in Denver pay a median of $184,000 across 153 tracked positions. That's 8% below the national 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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