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About This Role
Requisition ID: 49975
Business Unit: Fitch Learning
Category: Business Development \& Sales
Location:New York, NY, US
Date Posted: Jun 5, 2026
Fitch Learning is the leading provider of financial services education to the global financial markets. As we rapidly grow, Fitch Learning is seeking an AI Learning Sales Team Leader to lead and scale its AI\-focused sales capability within the financial services education industry. This newly created leadership role will drive enterprise revenue growth through AI\-enabled learning and SaaS\-based education solutions, developed by a highly dynamic AI learning business in which Fitch Learning is a strategic shareholder.
This role is ideal for a senior sales leader with experience in enterprise SaaS, AI\-driven solutions, and consultative selling, particularly within the context of workforce learning, professional education, or digital transformation in financial services.
About the Role:
Sitting within Fitch Learning, this position combines hands\-on sales leadership, deep AI and SaaS fluency, and team management. The successful candidate will play a key role in shaping and executing Fitch Learning's AI\-led learning proposition, built specifically for clients operating in complex financial services environments.
The role includes responsibility for managing and developing a team of up to four AI Learning Sales Specialists, while also directly leading strategic, high\-value client opportunities.
How You’ll Make an Impact:
AI Learning Sales Leadership
- Own and drive AI learning sales performance across enterprise clients in the financial services education market
- Lead complex, high\-value sales opportunities for AI\-enabled learning platforms and solutions
- Represent Fitch Learning’s AI learning proposition with senior clients and internal stakeholders
Strategic Client Ownership
- Manage a personal portfolio of strategic AI learning and SaaS opportunities
- Act as senior sales lead on priority enterprise deals, engaging at executive level
Team Leadership
- Lead, coach, and develop a team of up to four AI Learning Sales Specialists
- Build strong SaaS\-style sales discipline, including value\-based and consultative selling approaches
Senior Stakeholder Partnership
- Build trusted relationships with Senior Business Heads, Product, Marketing, and Delivery teamsPartner with Relationship Managers, who own the client relationship, to shape and win AI\-enabled learning deals
- Lead client conversations on AI governance, data privacy, and learning outcomes, positioning the credibility of Fitch\-verified content.
- Sales Discipline
- Maintain rigorous forecasting, pipeline management, and Salesforce hygiene
- Drive consistent performance against revenue and conversion targets
You May Be a Good Fit If:
- Proven senior B2B sales experience in SaaS, digital, or technology\-led solutions, with a personal track record of winning net\-new enterprise business
- Strong track record selling enterprise SaaS or platform\-based offerings
- Experience leading and developing high\-performing sales teams while personally carrying and closing strategic deals Excellent consultative, value\-based selling skills
- Strong communication, leadership, and stakeholder management capability
What Would Make You Stand Out:
- Experience with AI\-enabled, data\-driven, or intelligent SaaS platforms
- Exposure to enterprise learning, edtech, professional education, workforce transformation, or L\&D solutions
- Understanding of the financial services education sector would be a strong advantage
Success Measures
- AI learning sales revenue growth and pipeline performance
- Strategic deal conversion and forecast accuracy
- Team productivity, capability development, and sales execution quality
Why Choose Fitch:
- Hybrid Work Environment: 3 days per week in the office; 2 days remote
- A Culture of Learning \& Mobility: Dedicated training, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity
- Investing in Your Future: Retirement planning and tuition reimbursement programs that empower you to achieve your short and long\-term goals
- Promoting Health \& Wellbeing: Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing
- Supportive Parenting Policies: Family\-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively
- Inclusive Work Environment: A collaborative workplace where all voices are valued, with Employee Resource Groups that unite and empower our colleagues around the globe
- Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community
Fitch is committed to providing global securities markets with objective, timely, independent and forward\-looking credit opinions. To protect Fitch’s credibility and reputation, our employees must take every precaution to avoid conflicts of interest or any appearance of a conflict of interest. Should you be successful in the recruitment process at Fitch you will be asked to declare any securities holdings and other potential conflicts prior to commencing employment. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.
Fitch is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.
For New York: Expected base pay rates for the role will be between $190,000 to $200,000 per year. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job\-related factors. Base pay is one part of Fitch’s total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, long\-term incentives, and other benefits sponsored by Fitch.
\#LI\-MH1 \#LI\-HYBRID
Salary Context
This $190K-$200K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Fitch Learning, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($195K) sits 8% above the category median. Disclosed range: $190K to $200K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Fitch Learning AI Hiring
Fitch Learning has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $200K - $200K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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