Interested in this AI/ML Engineer role at Cotiviti?
Apply Now →Skills & Technologies
About This Role
Overview:
The Vice President, Sales is responsible for the development and strategic execution of annual sales plans to support the acquisition of new clients and sale of new solutions for the Cotiviti Retail division. This is a hunter role focused on hunting new business for Cotiviti’s Retail Payment Integrity Services and Solutions to the world’s largest retailers, e-commerce, and commercial enterprises. Demonstrated experience calling on and selling to “C” level executives, SVP Business Owners, CFO’s, Procurement, VPs, and Directors is essential. Experience working in a disruptive software and services sector selling Data Analytics, Payment Integrity / Recovery Auditing services and solutions.
Come join us, grow your career with a industry leader and help us take Cotiviti Retail to the next level of success!
Responsibilities:
- Direct prospecting (hunting) new business for Cotiviti’s Retail Payment Integrity Services and Solutions.
- Achieve or exceed Retail sales revenue and growth targets as defined by the organization’s leadership and strategic imperatives.
- Define and drive the business development process. Develop strategies, budgets, and accurate sales forecasts to execute business plans and deliver on commitments.
- Identify and convert sales opportunities in new accounts into closed business.
- Identify new market/customer opportunities for growth through prospecting, growth and competitive displacement.
- Establish multi-level relationships with potential customer decision makers and meet regularly to manage the sales process and reinforce Cotiviti’s relationship with the prospects.
- Maintains a target list of opportunities, updates customer profiles and provides accurate forecasts/pipeline tracking within the Cotiviti sales process and CRM.
- Collaborate within a heavily matrixed environment in order to leverage internal resources and external contacts to drive new business leads and referrals.
- Partner with the Business Unit, Product and Marketing organizations to bring new products to market, ensure successful launch and drive early sales.
Creates Value for Prospective Cotiviti Customers
- Invest sufficient time to develop a deep understanding of the prospect’s business strategy and critical business issues.
- Create unique value for prospective customers by seeking to understand their business problems, issues and opportunities in new or different ways.
- Link solutions and Cotiviti resources to identify customer needs and differentiate Cotiviti solutions from competing alternatives.
- Deliver a winning value proposition using customer metrics rather than product features.
- Develop and deliver sales solutions and customer presentations that result in increased sales by consistently and effectively reinforcing the company's value proposition and brand identity in distinctive and compelling ways.
- Ensure complete customer satisfaction from presales through post sales.
- Drive a sales culture where you link planning and strategy tools with selling and execution skills.
- Develop and implement key metrics to drive performance in total customer focus and account development.
- Driving individual performance through ongoing goal setting, results measurement, individual development, and deployment.
- Team Selling Partner with Strategic Account Managers to ensure effective account transition and post-sales support.
- Ensure that new and existing customers are transitioned to Strategic Account Managers in a manner that is non-disruptive to the customer’s operation, delivers on our commitments to them, and retains them as a customer.
Qualifications:
- Bachelor’s degree in Sales, Marketing, Business or related field required.
- Highly motivated individual with 5 to 10+years of demonstrated success in consultative/solution-based selling in a B2B environment within the industry.
- Excellent command of the selling process and a discipline to follow a sequence of events to close business.
- Experience selling at the senior management levels with a proven track record of routinely closing deals that are mutually beneficial to the customer and the Company.
- Outstanding interpersonal skills, highly effective communicator with excellent written and presentation skills.
- Experience with CRMs including MS Dynamics preferred.
- Ability to travel as required (25-50%).
Mental Requirements:
- Demonstrated ability to balance activities across multiple internal customers, campaigns, tasks, and performance pressures.
- Strong analytical skills with the demonstrated ability to research prospective customers and plan sales prospecting activities accordingly.
- Excellent oral and written skills.
- Strong interpersonal skills required. Understands that internal customers’ interests are best served through continuous prospecting and intelligence gathering activities and proactive communication with sales partners.
- Must be able to perform daily functions with little or no direct supervision.
- Communicating with others to exchange information.
- Assessing the accuracy, neatness, and thoroughness of the work assigned.
Physical Requirements and Working Conditions:
- Remaining in a stationary position, often standing or sitting for prolonged periods.
- Repeating motions that may include the wrists, hands, and/or fingers.
- Must be able to provide a dedicated, secure work area.
- Must be able to provide high-speed internet access/connectivity and office setup and maintenance.
- No adverse environmental conditions are expected.
*Base compensation ranges from $166,000 to $185,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.* *This role is eligible for commission.*
*Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our* *Careers page.*
*Since this job will be based remotely, all interviews will be conducted virtually.*
Date of posting: 1/23/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 5/1/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
#LI-Remote
#LI-AK1
#director
Salary Context
This $166K-$185K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Cotiviti, 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 $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($175K) sits 14% above the category median. Disclosed range: $166K to $185K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Cotiviti AI Hiring
Cotiviti has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $185K - $185K.
Remote Work Context
Remote AI roles pay a median of $160,000 across 1,226 positions. About 7% of all AI roles offer remote work.
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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.