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About This Role
Title: Head of Product Marketing & Communications, Precision Care AI
Reporting to: Chief Revenue Officer
Location: This role can be based remotely in the US or hybrid based out of our HQ in Bethesda, MD
Opportunity:
Get Well RhythmX (“GWRX”) is seeking a Head of Product Marketing & Communications, Precision Care AI to build and lead a modern, AI-first marketing organization that accelerates revenue growth, strengthens category leadership, and clearly communicates the real-world impact of our AI solutions at scale. The Head of Product Marketing & Communications, Precision Care AI to fundamentally redefine how the Company goes to market and shape industry leadership. The role will work in close collaboration with sales, product management, customer success, and other cross-functional teams. This role is not about traditional marketing activities, campaign execution, or legacy communications, but using AI as a force multiplier to:
- Deliver significant, measurable, sales-qualified pipeline
- Establish GWRX as the undisputed industry authority in Precision Care AI
- Replace slow, pre-AI marketing and communications methods with AI-first systems, workflows, and insights
- Translate complex AI, clinical, and operational value into credible, outcome-driven narratives that resonate with health system executives, clinical leaders, boards and C-suites, and industry analysts and influencers
Success in this role is measured by revenue impact, pipeline creation, and category leadership.
Responsibilities:
- Own marketing and communications’ contribution to enterprise pipeline, bookings influence, and ARR growth
- Design AI-driven GTM and communications strategies that generate measurable, sales-qualified pipeline
- Continuously optimize for pipeline quality, velocity, and conversion
- Aggressively apply AI to reinvent: Market and account segmentation, Account-based marketing and personalization, Content creation and distribution, Buyer and stakeholder insight discovery, and Competitive, analyst, and market intelligence
- Replace manual, pre-AI workflows with AI-enabled automation and augmentation
- Set the internal and external standard for what AI-first marketing and communications look like in healthcare
- Establish GWRX as the category-defining leader in Precision Care AI
- Build sustained credibility with a variety of stakeholders: Health system CEOs, CIOs, CMIOs, CFOs, and COOs, Clinical and operational leaders, and Industry analysts, media, and ecosystem partners
- Ensure GWRX is consistently associated with measurable outcomes and real-world impact, not abstract AI promises
- Translate AI capabilities, clinical workflows, and operational outcomes into clear, differentiated narratives
- Ensure every product launch, message, and proof point reinforces category leadership
- Partner deeply with Product, Engineering, and Customer Success to connect: AI innovation, customer outcomes, and revenue impact
- Make product marketing a strategic growth lever, not a support function
- Equip sales teams with AI-powered insights, messaging, and value models that materially improve win rates
- Enable sellers to speak credibly to clinical and executive stakeholders, quantify outcomes and ROI, and position GWRX as a long-term strategic partner
- Measure enablement success by sales performance, not asset volume
- Build and lead a lean, elite, AI-native product marketing and communications team
- Operate with startup speed, high accountability, and relentless focus on outcomes
- Set clear OKRs tied to pipeline, ARR influence, and market leadership
Requirements:
- 12+ years of enterprise marketing experience with experience leading a full-stack marketing team
- Healthcare IT background with deep understanding of health system buyers, clinical and operational workflows, complex enterprise sales cycles, and EHR integrated solutions
- Proven success scaling product-led, enterprise-grade marketing organizations tied to revenue outcomes
- Quantifiable lead generation through strong demand generation and outbound/inbound efforts; proven track record in directly contributing to revenue, not just top-line leads
- Strong command of product marketing, demand generation, sales enablement, brand strategy, and analyst relations
- Demonstrated experience using AI tools and data-driven insights to improve marketing performance materially
- Exceptional executive-level communication skills—written, verbal, and presentation.
- Highly analytical, outcome-oriented, and comfortable operating in fast-moving, ambiguous environments.
- Bachelor’s degree in Marketing, Business, Technology, or related field; MBA preferred.
- Adhere to all organizational information security policies and protect all sensitive information, including but not limited to electronic protected health information (ePHI), protected health information (PHI), personally identifiable information (PII), and Get Well information based on data classifications in accordance with organizational policy and Federal, State, local, and international regulations.
About GW RhythmX:
GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.
About SymphonyAI Group:
SymphonyAI Group (SAIGroup) is a private investment firm building leading global enterprise AI businesses by accelerating innovation and growth. SAIGroup companies ConcertAI, SymphonyAI, and GW RhythmX deliver AI solutions that transform industries and bring value to companies, workers, healthcare professionals, and patients. The companies collectively represent a workforce of more than 4,000 talented engineers, data scientists and industry/healthcare experts. SAIGroup is backed by a $1 billion commitment from Founder and CEO Dr. Romesh Wadhwani, a noted entrepreneur and philanthropist. Learn more at www.saigroup.ai and follow SAIGroup on LinkedIn.
When it comes to careers, our approach is simple: empower employees to do their best work and live their best professional and personal lives. Meeting the needs of a diverse group of employees across more than 30 states means offering tools to support financial, physical and emotional well-being and the choice to design what meets your needs. You’ll find everything you’d expect and many things you don’t: exceptionally generous paid time away from work, a variety of paid leave programs, savings opportunities with 401(k) and incentive plans, internal education programs, full array of health benefits, fitness reimbursement, cell phone subsidy, casual offices with snacks and drinks, peer recognition programs, health advocacy and employee assistance programs, chili cook-offs, pet insurance (yes, really) and so much more. Our most valuable benefit? An environment that supports YOU. The estimated pay range for this position is $220,000 - $260,000 in base salary plus bonus. Base salary is dependent on many factors including, but not limited to education, experience and skills. This range is subject to change and may be modified in the future.
Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.
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Salary Context
This $220K-$260K range is above the 75th percentile 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 GetWellNetwork, 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. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($240K) sits 56% above the category median. Disclosed range: $220K to $260K.
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.
GetWellNetwork AI Hiring
GetWellNetwork has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $260K - $260K.
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
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