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About This Role
As an AI Engineering Manager at Solstice, you will play a pivotal role in driving AI initiatives across various business functions using multiple technology platforms. You will translate cutting\-edge AI \& Automation research into practical enterprise solutions while collaborating with technical and business teams to maximize AI's transformative impact on operational efficiency and strategic outcomes.
You will report to our Director IT, AI, Analytics \& Automation who oversees our enterprise data strategy, delivery and platform operations.
This position is ideal for a strategic thinker \& doer who can bring automation, process optimization and Agentic AI together driving digital transformation to new frontiers by moving from insights to action with AI/ Gen AI advances.
You will work out of the Morris Plains, NJ location.
About Solstice Advanced Materials
Solstice Advanced Materials is a leading global specialty materials company that advances science for smarter outcomes. Solstice offers high\-performance solutions that enable critical industries and applications, including refrigerants, semiconductor manufacturing, data center cooling, nuclear power, protective fibers, healthcare packaging and more. Solstice is recognized for developing next\-generation materials through some of the industry's most renowned brands such as Solstice®, Genetron®, Aclar®, Spectra®, Fluka™, and Hydranal™. Partnering with over 3,000 customers across more than 120 countries and territories and supported by a robust portfolio of over 5,700 patents, Solstice’s approximately 4,000 employees worldwide drive innovation in materials science. For more information, visit Advanced Materials .
You will identify new opportunities for Automation by analyzing business processes, develop new automation solutions, ensure the successful execution of automation bots \& AI agents and enhance operational efficiency. This role will significantly impact our automation strategy by bridging technical capabilities with business needs.
KEY RESPONSIBILITIES
- Technical Expertise \& Delivery: Serve as a versatile hands\-on subject matter expert across AI/ Gen AI technologies with a comprehensive understanding of both technical processes and business operations to delivery enterprise grade solutions. Implement the MLOps/LLMOps, Cloud DevSecOps practice \& package AI solutions for production.
- Service Delivery Leadership: Lead the design, build, and implement enterprise AI Systems that meet complex business requirements while ensuring scalability, performance, and alignment with enterprise objectives. Oversee Gen AI, Classical and Automation initiatives across Enterprise functions such as Supply Chain, Finance, Commercial, Customer Experience, Legal, HR and others.
- Own Speed to Delivery: Accelerate Applied AI Initiatives by creating a rapid iteration loop from idea to execution in line with responsible AI principles. Guide and technically steer Corporate AI Risk Council balancing risk, compliance and speed for Gen AI adoption. Drive evaluation \& observability first mindset bringing Gen AI reliability to the center stage. Strategize around creating a robust data flywheel ensuring a roadmap for continuous learning systems
- Cross\-Functional Collaboration: Partner across business, technology, architecture, and security teams to identify automation opportunities and deliver secure, scalable AI solutions. Develop practical standards and guidance for responsible, classification\-aware AI and Gen AI adoption.
- Raise the AI Bar: Translate and align key research \& engineering advancements in AI into actionable strategy for Solstice Advanced Materials, pushing the envelope with state of art, robust \& reliable enterprise ready AI solutions.
YOU MUST HAVE
- Minimum 8 years of progressive experience in AI solution delivery, with a demonstrated impact across multiple functional domains.
- Strong understanding of core AI concepts, including both foundational principles and hands\-on practical applications with demonstrated experience of productionizing enterprise grade solutions.
- Proficiency in multiple AI/ML \& Automation tools such as Azure AI / Microsoft Foundry, Databricks, Cognitive services \& Bot frameworks, Microsoft Power Platform, Workato, OutSystems, Automation Anywhere or similar, with a strong understanding of AI concepts and their application in automation.
- Experience integrating with enterprise platforms such as SAP, SFDC, HCM and other similar enterprise applications to create seamless AI \& automation solutions.
- Proven track record in developing, architecting end\-to\-end AI \& Automation solutions that integrate multiple systems and deliver measurable business value.
WE VALUE
- Python experience for AI/ML workflows strongly preferred.
- Experience building agent\-based systems with tool use, reasoning workflows, and API orchestration.
- Experience developing AI applications with LLM integrations, prompt engineering, and orchestration frameworks. Solid understanding of AI security practices including RBAC/ABAC, audit logging, and prompt\-level safeguards
- Experience optimizing vector databases and semantic search technologies for large datasets.
- Experience with compound AI architectures, retrieval pipelines, and Azure/Databricks DevOps or MLOps practices.
- Experience integrating AI solutions into enterprise channels such as Teams, Web Chat, or Direct Line.
- Ability to quickly understand new functional domains, technical environments, business processes, and requirements, and translate them into effective automation solutions.
- Exceptional analytical thinking and creative problem\-solving skills in complex technical and business contexts. Ability to translate AI technical concepts for audiences at various levels.
- Ownership and Pride in your work and willingness to work in a diverse, cross\-functional environment. Attention to detail.
- Proven ability to partner with diverse stakeholders, identify automation improvements, and understand data needs across discrete and continuous manufacturing processes.
- Experience of working closely with managed services providers to ensure effective support and management of automation processes.
- Prior publication record in top tier journals or conferences such as NeurIPS, AAAI, EMNLP, MICA or similar.
COMPENSATION
The annual base salary range for this position is $201\-063\-251,622\. Please note that this salary information serves as a general guideline. Solstice considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations.
BENEFITS OF WORKING FOR SOLSTICE ADVANCED MATERIALS
In addition to a competitive salary, leading\-edge work, and developing solutions side\-by\-side with dedicated experts in their fields, Solstice Advanced Materials employees are eligible for a comprehensive benefits package. This package includes employer\-subsidized Medical, Dental, Vision, and Life Insurance; Short\-Term and Long\-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays.
*Solstice Advanced Materials is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.*
Salary Context
This $131K-$418K range is above the 75th percentile for AI Engineering Manager roles in our dataset (median: $185K across 13 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 4,317 AI roles we're tracking, AI Engineering Manager positions make up 0% of the market. At Solstice Advanced Materials, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Engineering Manager roles pay a median of $244,000 based on 23 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($274K) sits 13% above the category median. Disclosed range: $131K to $418K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Solstice Advanced Materials AI Hiring
Solstice Advanced Materials has 2 open AI roles right now. They're hiring across AI Engineering Manager, Data Scientist. Based in Morris Plains, NJ, US. Compensation range: $211K - $418K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Engineering Manager roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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