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About This Role
$175,000 - $210,000 + Bonus 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.
$175,000 + $210,000 + Bonus
The insurance industry runs on Vertafore. We equip agencies, MGAs, and carriers with the core digital systems, specialized AI, and data-driven foundation to eliminate distribution drag across the insurance lifecycle, spanning sales, servicing, and back-office operations.
Underpinned by unmatched speed and performance power, we are the trusted backbone that’s taking the insurance industry from friction to flow with Distribution Velocity – speed, performance, and trust - to drive growth at scale.
With over 95% of the top agencies and insurers and 50% of industry compliance transactions running through Vertafore, we lead at the intersection of innovation and trust, giving insurance professionals the confidence to transform and win in the AI era.
Our reach is global, with headquarters in Denver, Colorado, and offices across the U.S., Canada, and India.
About the Role
As a Senior AI Engineer, you will design, build, and operate the AI systems behind Vertafore’s next generation of products for agencies, MGAs, and carriers. You will build production-grade agents that can reason through complex, multi-step insurance workflows, and you will be responsible for making those systems reliable, measurable, and safe in a highly regulated industry.
You will work in small pods with complete agency to build end to end products. This role is hands-on. You’ll be expected to directly contribute to the successful implementation and launch of critical features and empowered to make the decisions needed to get there. Vertafore designs these pods as end to end development teams so fluidity going up and down the stack is expected.
We are looking for an engineer who is strong in software and systems engineering, understands machine learning well, and has a habit of shipping. You use the latest agentic coding tools to work faster, and you hold yourself fully accountable for the quality, security, and correctness of what you ship.
Core Requirements and Responsibilities:
Essential job functions included but are not limited to the following:
- Design, build, and deploy complex reasoning agents and multi-agent systems for production workloads using LangGraph and related Python orchestration frameworks
- Architect agent workflows, including state management, tool use, memory, planning, human-in-the-loop checkpoints, error recovery, and fallback behavior
- Design and build clean, well-documented, versioned APIs that expose AI capabilities to Vertafore products and to external partners
- Define and own evaluation strategy for AI systems. This includes building eval datasets, writing graders (programmatic, model-based, and human review), running offline and online evaluations, and turning results into concrete improvements
- Set up regression testing for prompts, models, and agent behavior so that changes ship with measurable confidence
- Instrument AI systems for observability, including tracing, latency, cost, token usage, failure modes, and quality metrics in production
- Build retrieval and context pipelines (RAG, document processing, structured extraction) over insurance data such as policies, submissions, and compliance documents
- Troubleshoot and resolve production issues across the AI stack, from model behavior to infrastructure
Knowledge, Skills and Abilities:
- Expert-level Python, including writing idiomatic, typed, tested, production-quality code and using async programming
- Solid understanding of ML fundamentals, including model training and generalization, overfitting, bias and variance, embeddings, classification and ranking metrics, and statistical significance
- Deep understanding of how large language models behave in practice, including failure modes, non-determinism, context limits, and strategies for reliable outputs
- Rigorous, experimental mindset; you form hypotheses, measure, and let data drive decisions rather than intuition about model output
Basic Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or a related field, or equivalent practical experience
- 7+ years of professional software engineering experience, with significant time building backend services and systems in Python
- 2+ years building and shipping LLM-powered applications or agentic systems to production
- Hands-on production experience with LangGraph (or comparable agent orchestration frameworks such as LangChain, LlamaIndex, or custom orchestration)
- 5+ years designing and building RESTful APIs (experience with FastAPI or similar frameworks preferred)
- Demonstrated experience designing and running evaluations for ML or LLM systems, and using results to drive measurable quality improvements
- Experience with cloud platforms (AWS preferred), Docker, and CI/CD pipelines
Preferred Qualifications:
- Experience with LLM observability and evaluation tooling (such as LangSmith, Langfuse, Braintrust, or similar)
- Experience with fine-tuning, embedding model selection, or classical ML pipelines
- Experience in insurance, financial services, healthcare, or another regulated industry
- Experience with Model Context Protocol (MCP) or building tool integrations for agents
- Open-source contributions or public writing on AI engineering
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.
Salary Context
This $175K-$210K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% 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 $212,040 based on 13,780 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($192K) sits 9% below the category median. Disclosed range: $175K to $210K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Vertafore AI Hiring
Vertafore has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $210K - $210K.
Location Context
AI roles in Denver pay a median of $200,000 across 143 tracked positions. That's 6% 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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