Interested in this AI/ML Engineer role at United Concordia Dental?
Apply Now →About This Role
Company :
-------------
enGen
Job Description :
---------------------
JOB SUMMARY
The VP AI Strategy \& Enablement is responsible for defining and driving the strategic direction and operational execution of Artificial Intelligence capabilities within enGen and across the Highmark enterprise. This role is pivotal in leveraging advanced AI and cloud technologies to foster innovation, create business value, and enhance operational efficiencies, ultimately contributing to new revenue streams and strategic differentiation for Highmark and enGen. The VP will act as a key liaison, fostering strong partnerships and influencing stakeholders at all levels of the organization to champion AI adoption and integration.
ESSENTIAL RESPONSIBILITIES
- Perform management responsibilities to include, but are not limited to: involved in hiring and termination decisions, coaching and development, rewards and recognition, performance management and staff productivity. Plan, organize, staff, direct and control the day\-to\-day operations of the department; develop and implement policies and programs as necessary; may have budgetary responsibility and authority.
- AI Strategy and Vision Leadership: Own the development, communication, and execution of the enGen AI roadmap, aligning with the broader enterprise AI strategy and business unit expectations.
- AI Program and Adoption: Drive AI adoption and programs within enGen and across the enterprise, fostering a culture of innovation and data\-driven decision\-making. This includes leading the deployment of short\-and\-long\-term technological innovations, specifically cloud technologies and AI capabilities.
- Commercialization and Revenue Generation: Commercialize enGen's AI capabilities to identify and seed new revenue streams, demonstrating tangible business value and strategic growth opportunities.
- Cross\-Enterprise Collaboration: Create and nurture strong partnerships across the enterprise and within enGen. This involves effectively presenting complex AI topics in a concise manner that will influence multiple stakeholders and support functions to listen, commit, and act.
- Operational Excellence and Compliance: Deliver flexible, high\-quality AI solutions and operational frameworks that adhere to privacy policies, mandates, and regulations. Continuously improve AI development processes and technology in line with time parameters and budget expectations.
- Other duties as assigned or requested.
EDUCATION
Required
- Bachelor's Degree in STEM field
Preferred
- Master's Degree in Business Administration, Management Information Science, or related field
Substitutions
- 13\+ years of highly relevant leadership experience in large enterprises could be substituted for Master's Degree preference
EXPERIENCE
Required
- 7 years of management or leadership role
- 7 years leading data engagements directly with internal and commercial clients
Preferred
- Experience managing complex initiatives in the consulting, healthcare, or insurance industry
- Track record of driving transformational change, leading teams, developing talent, and building relationships
- Experience running profit and loss center
- Understanding of Agile Development techniques and tools
LICENSES OR CERTIFICATIONS
Require
- None
SKILLS
- Comprehensive applied knowledge managing scaled AI platforms and solutions.
- Ability to manage diverse set of executive stakeholders, building consensus while driving strategy forward.
- Deep healthcare data comprehension, including regulatory and compliance complexity.
- Strong strategic thinking and ability to translate business needs into AI solutions.
SCOPE OF RESPONSIBILITY
Does the role supervise/manage other employees?
Yes
WORK ENVIRONMENT
Is Travel Required?
Yes \- less than 25%
*Disclaimer:* *The job description has been designed to indicate the general nature and essential duties and responsibilities of work performed by employees within this job title. It may not contain a comprehensive inventory of all duties, responsibilities, and qualifications required of employees to do this job.*
*Compliance Requirement:* *This position adheres to the ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies.*
*As a component of job responsibilities, employees may have access to covered information, cardholder data, or other confidential customer information that must be protected at all times. In connection with this, all employees must comply with both the Health Insurance Portability Accountability Act of 1996 (HIPAA) as described in the Notice of Privacy Practices and Privacy Policies and Procedures as well as all data security guidelines established within the Company’s Handbook of Privacy Policies and Practices and Information Security Policy.*
*Furthermore, it is every employee’s responsibility to comply with the company’s Code of Business Conduct. This includes but is not limited to adherence to applicable federal and state laws, rules, and regulations as well as company policies and training requirements.*
Pay Range Minimum:
$209,000\.00
Pay Range Maximum:
$372,000\.00
*Base pay is determined by a variety of factors including a candidate’s qualifications, experience, and expected contributions, as well as internal peer equity, market, and business considerations. The displayed salary range does not reflect any geographic differential Highmark may apply for certain locations based upon comparative markets.*
Highmark Health and its affiliates prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities and prohibit discrimination against all individuals based on any category protected by applicable federal, state, or local law.
We endeavor to make this site accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact the email below.
For accommodation requests, please contact HR Services Online at HRServices@highmarkhealth.org
California Consumer Privacy Act Employees, Contractors, and Applicants Notice
Salary Context
This $209K-$372K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At United Concordia Dental, 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 in Demand for This Role
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 $218,750 based on 3,817 positions with disclosed compensation. This role's midpoint ($290K) sits 33% above the category median. Disclosed range: $209K to $372K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
United Concordia Dental AI Hiring
United Concordia Dental has 2 open AI roles right now. They're hiring across AI Architect, AI/ML Engineer. Based in PA, US. Compensation range: $196K - $372K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.