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About This Role
Overview:
As a Senior Software Engineer on the AI Engineering Team at Cotiviti, you will contribute to the
development and delivery of AI/ML solutions for healthcare applications. This experienced professional position develops, tests, and implements scalable solutions, collaborates with data scientists and engineers, and provides knowledge sharing and support to team members. Responsibilities:
- Develop and implement machine learning solutions for healthcare applications.
- May provide knowledge sharing and support to team members.
- Collaborate with data scientists and other engineers to design and build scalable solutions.
- Write, test, and maintain high-quality code along with Code coverage.
- Participate in design and code review sessions.
- Troubleshoot and resolve complex technical issues.
- Document your work and share knowledge with the team.
- Apply established development standards and best practices.
- May assist with onboarding or knowledge transfer activities.
- Complete all responsibilities as outlined in the annual performance review and/or goal setting.
- Complete all special projects and other duties as assigned.
- Must be able to perform duties with or without reasonable accommodation.
This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change. Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Math, or a related field, or equivalent experience.
- 5+ years’ experience of developing AI/ML solutions.
- Strong programming skills in Python, and machine learning frameworks such as TensorFlow, Keras, or PyTorch.
- Working knowledge of data mining and statistical analysis/predictive analytics.
- Ability to solve problems with analytical thinking and the ability to conceptualize, design, and build models from scratch.
- Hands-on experience in defining and designing the models for predictive analytics based on business requirements.
- Deep understanding of data architecture principles, have good experience with different data sources and databases like Oracle, and MS SQL Server.
- Hands-on experience building CI/CD pipelines for production deployment of models. Hands-on experience with ML Ops is an added advantage.
- Experience with cloud-based ML/data services (AWS, Azure, or GCP).
- Experience working with generative AI/LLM frameworks and tools (e.g., LangChain, Hugging Face, vector databases, RAG pipelines, LLM APIs).
- Understanding in Agile, SDLC.
- Strong analytical and problem-solving skills.
- Familiarity with Agile processes and tools like Jira and Confluence.
- Strong drive to learn and advocate for development best practices, must be a team player with the ability to manage multiple tasks in a deadline driven environment.
- Knowledge in the Healthcare Insurance sector is an added advantage.
Cognitive/Mental Requirements* Curious: You are always looking to deepen your understanding of complex problems.
- Creative: You enjoy coming up with innovative solutions to difficult challenges.
- Practical: You focus on delivering solutions that have real-world applications and value.
- Focused: You maintain a clear vision of your goals and work diligently to achieve them.
- Determined: You are committed to contributing to the development of advanced machine learning capabilities.
Physical Requirements and Working Conditions* Must be available during normal business hours.
- Must be flexible to extend beyond the normal business hours based on project need.
- Must be able to provide high-speed internet access / connectivity and office setup and maintenance.
- Repeating motions that may include the wrists, hands, and/or fingers.
- Must be able to provide a dedicated, secure work area.
- No adverse environmental conditions are expected.
Base compensation ranges from $132,000 to $155,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. 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. This role is based remotely and all interviews will be conducted virtually.
Date of posting:09/28/2026 Applications are assessed on a rolling basis. We anticipate that the application window will close on 11/28/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
#LI-Remote #senior #LI-MC1
Salary Context
This $132K-$155K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Cotiviti, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($143K) sits 35% below the category median. Disclosed range: $132K to $155K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Cotiviti AI Hiring
Cotiviti has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Engineer. Based in Remote, US. Compensation range: $155K - $180K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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