Manager Data Engineering AI

$145K - $175K Remote Mid Level Data Engineer

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Skills & Technologies

AwsLangchainPrompt EngineeringRag

About This Role

AI job market dashboard showing open roles by category

Overview:

We are seeking an experienced Manager, Engineering- AI to lead our data engineering team. This individual will play a crucial role in overseeing the development of strategic perspectives regarding IT architecture and business needs. The Manager of Engineering will develop and implement data architecture and engineering strategies leveraging innovations in AI while exemplifying strong software development experience when working in an Agile environment. This individual will provide guidance to employees in accordance with established policies and management directives.

Responsibilities:

  • Will quickly possess an understanding of Cotiviti and is adept at working across organizational boundaries partnering with Business Leads and Functional Product Managers while maintaining a strategic perspective regarding IT architecture and business needs.
  • Drive, develop, and implement a data engineering architecture leveraging AI to ensure alignment with company performance objectives.
  • Drive, develop and implement templates, reference architectures and patterns with respect to implementing modern data engineering architecture pipelines connecting data sources on prem and within the cloud
  • Partner with Architecture and Product teams and contribute to the data product strategy, enhance data literacy of the several data assets within Cotiviti
  • Stay on top of the AI trends to ensure that we are leveraging them to ensure data engineering team efficiency, productivity and architectural relevance
  • Responsible for managing internal stakeholders and speaking with the client on behalf of the organization as needed.
  • Responsible for managing and evaluating staff performance for professional development of the staff members to include: conducting objective-setting goals, coaching, assessment, and mentoring activities.
  • The Manager will have significant latitude in defining results, selecting alternatives, and taking action across a range of products.
  • Will have primary knowledge, control, and influence of IT decisions for his/her area of responsibility, including optimizing service costs through a mix of internal and external resources for all aspects of development.
  • Working with the HIPAA Privacy and Security Officer and HIPAA Security Compliance team, ensuring all information systems and networks operate according to internal standards, external accrediting agency standards, regulatory agencies and legal requirements. In coordination with key personnel, develop and implement the following plans: disaster plan, emergency mode operation plan, backup plan, physical security plan, personnel security plan, access policies, and others. Ensure each plan is tested and revise plans as necessary to ensure data integrity, confidentiality, and availability.
  • Hire, develop, coach, lead and retain top-tier talent, with a focus on building and improving a team and culture that is able to assist in employing best in class practices to support and drive high levels of internal and external customer satisfaction.
  • 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 or equivalent work experience
  • 7+ years of total data engineering/IT/Project Management experience out of which at least 2 years must be management experience.
  • 2+ years’ experience leading small to mid-size projects through application of Project Management methodologies and artifacts.
  • 4+ years’ experience with data sets, Hadoop, Spark and/or other data integration/ETL tools like databricks, AWS tech stack, snowflake etc
  • 2+ years of experience working on AI engineering concepts and tools like RAG, Prompt Engineering, Langchain, LangGraph etc
  • Familiarity with ML Ops and LLM Ops capabilities and tools like Datarobot
  • 2+ years of hands-on experience in software development and database management.
  • Proficiency in Microsoft Office Suite.

Preferred Qualifications:* Experience with healthcare data preferably in a data operations role.

  • Experience working in an Agile environment.

Cognitive/Mental Requirements:

  • Ability to communicate simple and complex messages to the team in a manner that is clear, persuasive, and sincere.
  • Ability to summarize complex and/or technical information into easy-to-understand pieces, distinguishing message delivery from analysis.
  • Ability to apply organizational, industry knowledge to facilitate process improvement that optimizes functional area to positively impact strategic initiatives of the department and organization.
  • Ability to win trust and confidence of team members even when dealing with unpopular decisions.
  • Ability to lead and motivate team through day to day as well as during unclear or challenging conditions.
  • Ability to provide big picture vision, align goals with larger department and organizational ones.
  • Ability to develop well rounded skill sets regarding business, technical and interpersonal skills.
  • Ability to adjust quickly to changing assignments, processes and people while identifying opportunities to further growth and development of self and processes.
  • Ability to proactively manage and resolve conflict, help team find a ‘win-win’ solution.
  • Ability to break down silos that impact cooperations and partnership.
  • Ability to value team members as individuals while embraces differences.
  • Ability to deploy variety of techniques to establish rapport, gain commitment from and adapt to the decision-making styles of executives, department leaders and outside groups.
  • Ability to accomplish goals by setting appropriate objectives and planning effectively while monitoring plans and adjusting as needed to keep plans realistic and focused.
  • Ability to prioritize tasks against business prioritize, effectively manage time against priorities to accomplish them and allocate resources affectively to meet deadlines.
  • Ability to make sound situational decisions even in absence of precedent or experience.

Working Conditions and Physical Requirements:

  • 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.

Pay Transparency:

Base compensation ranges from $145,000.00 to $175,000.00. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. This role is eligible for discretionary bonus consideration.

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: 9/21/2026 Applications are assessed on a rolling basis. We anticipate that the application window will close on 11/21/2026 but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.

Salary Context

This $145K-$175K range is above the median for Data Engineer roles in our dataset (median: $151K across 28 roles with salary data).

Role Details

Company Cotiviti
Title Manager Data Engineering AI
Location Remote, US
Category Data Engineer
Experience Mid Level
Salary $145K - $175K
Remote Yes

About This Role

Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.

The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.

Across the 9,653 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Cotiviti, this role fits into their broader AI and engineering organization.

Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.

What the Work Looks Like

A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.

Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.

Skills Required

Aws (9% of roles) Langchain (3% of roles) Prompt Engineering (4% of roles) Rag (7% of roles)

SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.

AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.

Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.

Compensation Benchmarks

Data Engineer roles pay a median of $177,825 based on 160 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($160K) sits 10% below the category median. Disclosed range: $145K to $175K.

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 Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.

From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.

Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.

What to Expect in Interviews

Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.

When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.

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).

Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.

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

Based on 160 roles with disclosed compensation, the median salary for Data Engineer positions is $177,825. Actual compensation varies by seniority, location, and company stage.
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
About 6% of the 9,653 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Cotiviti is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Data Engineer positions include Senior Data Engineer, ML Engineer, Data Platform Lead. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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