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About This Role
Customer Event \& Benefit Education Fulfillment Supervisor
Organization: Support Resolution Center (SRC)
Workstream: Customer Event Operations / Benefit Education
Opening Statement
Bring your leadership skill, operational mindset, and passion for customer engagement to a role where your work makes a real difference. As the Customer Event \& Benefit Education Fulfillment Supervisor, you will lead with purpose—guiding a talented team, partnering across the business, and rolling up your sleeves to ensure customer events are delivered with quality, consistency, and care. This is an opportunity to grow people, strengthen processes, and help scale a customer event support model that reflects our commitment to being ambitious, compassionate experts.
Responsibilities
- Drive successful customer event delivery by serving as the primary point of contact between the Support Resolution Center and Customer Event Operations.
- Lead, coach, and develop Benefit Education Leads to consistently deliver high\-quality customer event support and positive experiences.
- Balance people leadership with hands\-on execution by actively performing Benefit Education Lead work and modeling best practices.
- Ensure end\-to\-end coordination of customer events, including scheduling, logistics, materials, and clear stakeholder communication.
- Strengthen operational alignment by partnering with internal teams and contributing to the ongoing evolution of the Salesforce Field Service Tool.
- Collaborate closely with sales, account teams, producers, vendors, and matrix partners to support seamless customer\-facing events.
- Optimize team capacity by planning workloads, aligning resources, and supporting volume shifts across SRC workstreams.
- Resolve complex or non\-routine event challenges by escalating thoughtfully and partnering with SRC leadership when needed.
- Promote consistent standards by ensuring adherence to customer event guidelines, timelines, and service expectations.
- Identify opportunities to improve workflows, coordination, and processes that support scalability and efficiency.
- Support reporting and tracking to provide visibility into customer event activity, outcomes, and trends.
- Champion accountability, quality, and continuous improvement across customer event support.
Qualifications
Required Qualifications
- Minimum of 5 years of experience in customer event coordination, benefit education, customer engagement, or a related operational support role.
- At least 2 years of experience in a supervisory, team lead, or peer leadership capacity.
- Proven ability to lead through influence while also executing work independently.
- Strong organizational and time management skills with the ability to manage multiple priorities.
- Clear, confident written and verbal communication skills.
- Demonstrated success collaborating within a highly matrixed organization.
- Proficiency with Microsoft Outlook, Word, Excel, and PowerPoint.
- Ability to build trusted relationships and serve as a central coordination and escalation partner.
Preferred Qualifications
- Bachelor’s degree or equivalent experience.
- Experience supporting or leading Benefit Education Leads, Customer Event Operations, or similar customer\-facing event teams.
- Experience in a working supervisor role that blends people leadership with hands\-on execution.
- Strong understanding of customer event logistics, scheduling, materials coordination, and stakeholder communication.
- Demonstrated ability to coach, mentor, and develop team members.
- Experience contributing to process improvement, standardization, or operational scaling initiatives.
- Familiarity with Salesforce or similar workflow and case management tools.
- Exposure to health benefits, healthcare, or enrollment\-related customer engagement activities.
If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.
For this position, we anticipate offering an annual salary of 63,100 \- 105,100 USD / yearly, depending on relevant factors, including experience and geographic location.
This role is also anticipated to be eligible to participate in an annual bonus plan.
At The Cigna Group, you’ll enjoy a comprehensive range of benefits, with a focus on supporting your whole health. Starting on day one of your employment, you’ll be offered several health\-related benefits including medical, vision, dental, and well\-being and behavioral health programs. We also offer 401(k), company paid life insurance, tuition reimbursement, a minimum of 18 days of paid time off per year and paid holidays. For more details on our employee benefits programs, click here.
About Cigna Healthcare
Cigna Healthcare, a division of The Cigna Group, is an advocate for better health through every stage of life. We guide our customers through the health care system, empowering them with the information and insight they need to make the best choices for improving their health and vitality. Join us in driving growth and improving lives.*Qualified applicants will be considered without regard to race, color, age, disability, sex, childbirth (including pregnancy) or related medical conditions including but not limited to lactation, sexual orientation, gender identity or expression, veteran or military status, religion, national origin, ancestry, marital or familial status, genetic information, status with regard to public assistance, citizenship status or any other characteristic protected by applicable equal employment opportunity laws.*
*If you need a reasonable accommodation to complete the online application process, please email* *seeyourself@thecignagroup.com* *for assistance. Please note that this email inbox is dedicated to accommodation requests only and cannot provide application updates or accept resumes.*
*The Cigna Group has a tobacco\-free policy and reserves the right not to hire tobacco/nicotine users in states where that is legally permissible. Candidates in such states who use tobacco/nicotine will not be considered for employment unless they enter a qualifying smoking cessation program prior to the start of their employment. These states include: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maryland, Massachusetts, Michigan, Nebraska, Ohio, Pennsylvania, Texas, Utah, Vermont, and Washington State.*
*Qualified applicants with criminal histories will be considered for employment in a manner* *consistent with all federal, state and local ordinances.*
Salary Context
This $63K-$105K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At The Cigna Group, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($84K) sits 50% below the category median. Disclosed range: $63K to $105K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
The Cigna Group AI Hiring
The Cigna Group has 11 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Remote, US, CT, US, Philadelphia, PA, US. Compensation range: $54K - $297K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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