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About This Role
- Standort(e):
- White Plains, NY, US, NY 10606
RWE Americas, LLC
To start as soon as possible, full time, permanent
Functional area: IT / Digital
Remuneration: Exempt
The AI Engineer is a technical talent responsible for building and operating production\-grade AI applications within the architectural standards and patterns established by the platform architect.
This role leads the development of agentic AI systems, deploying scalable solutions in alignment with enterprise architecture and security standards, and translating prototypes built by data scientists and technical product managers into maintainable, monitored production services.
The AI Engineer drives engineering excellence in the squad by developing reusable components, patterns, and standards, and owns model health monitoring, post\-deployment diagnostics, and structured remediation to ensure sustained AI performance at scale.
Role Responsibilities:
- Design and build AI applications tightly integrated with enterprise data and systems, leading end\-to\-end development across the full stack from data ingestion through model serving and application layer
- Develop agentic AI systems incorporating tool use, multi\-step workflows, and robust guardrails, ensuring systems are reliable, auditable, and aligned with enterprise security standards
- Ensure AI solutions are deployed in alignment with enterprise architecture and security standards
- Work with AI Ops team to monitor model health post\-deployment, diagnosing drift and degradation with structured remediation plans, and implementing automated alerting and observability frameworks to ensure sustained system performance
- Implement reusable components and shared libraries aligned with the patterns and standards defined by the platform architect, contributing practical engineering feedback to refine/evolve platform standards over time
Job Requirements and Experience:
- Master’s or PhD degree in computer science, data science, STEM, or related field required
- Minimum 5 years of relevant professional experience in software or AI/ML engineering roles, with demonstrated experience building and deploying production\-grade AI applications in enterprise environments
- Deep knowledge of enterprise\-scale AI and software architecture, with strong proficiency in relevant ML/AI frameworks
- Strong experience developing and deploying agentic AI systems/solutions with tool use, RAG frameworks, multi\-step reasoning, and guardrail implementation, ensuring robustness and auditability in production environments
- Solid understanding of model performance monitoring, drift detection, and post\-deployment diagnostics, with experience implementing automated observability and structured remediation processes
- Experience partnering with technical product managers to translate experimental models into production ready services
- Independent ownership of strategic technical solutions, with the ability to mentor mid\-level engineers, promote engineering standards, and lead proof\-of\-concept initiatives
- Effective collaboration with data infrastructure stakeholders to align AI engineering with enterprise data and platform strategies
- Proactive and quality\-focused, driving continuous improvement through reusable components, shared patterns, and documentation that accelerates development across squads
- Experience with IT/OT environments, industrial data sources, or operational technology systems preferred
- Familiarity with responsible AI practices, security controls, and compliance requirements applicable to enterprise AI deployments preferred
- Experience in the power, utilities, or clean energy sector, including knowledge of U.S. power markets, renewable project development, and clean energy technologies preferred
- This position is an office\-based role with some travel and visits to other RWE Americas offices and field locations
- Must be able to sit, walk, or stand for long durations of time
*Applicants must be legally authorized to work in the United States. RWE Americas is unable to sponsor or take over sponsorship of employment visas at this time.*
Pay range: The annual base salary range for this position in New York is $125,000 \- $188,000\. The listed salary range represents our good faith estimate for this position and represents the range for new hire salaries across all U.S locations. Please note that the salary information is a general guideline only. RWE considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s education \& work experience, training \& certifications, and key skills as well as market and business considerations at the time of the offer.
Benefits offered: Medical, Dental, Vision, Life Insurance, Short\-Term Disability, Long\-Term Disability, 401(k) match, Flexible Spending Accounts, EAP, Education Assistance, Parental Leave, Paid time off, and Holidays. Eligible employees also participate in short\-term incentives, in addition to salary.
Apply with just a few clicks: ad code 92646\. Any questions? Contact HR: rwe\_americas\[email protected]
We look forward to meeting you. Of course, you can find us on LinkedIn, Instagram, Facebook, YouTube and Xing, too.
All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.
RWE Americas, a subsidiary of RWE, is a US\-based energy company that is helping to meet the growing demand for energy across the United States. Backed by RWE’s 125\-year global legacy of managing diverse power assets, RWE Americas operates approximately 13 GW of power projects across 27 states. With a talented workforce of 2,000 employees, RWE Americas develops, constructs and operates wind, solar and battery storage projects that safely deliver affordable, reliable electricity to our customers. Committed to responsible development, RWE Americas invests in local and rural communities, creating jobs and partnering with stakeholders to support and strengthen the places where we live and work. Learn more about how RWE Americas is generating impact at americas.rwe.com.
At RWE Americas, we foster a culture defined by our Essential Behaviors – Have Courage, Create Impact and Actively Collaborate. We encourage bold thinking and continuous learning, and we value ownership, resilience and inclusion in everything we do. When you join us, you become part of a team that supports your development, respects your contributions and celebrates shared success. This is a place where you can grow your career and make a meaningful difference.
Salary Context
This $125K-$188K range is below 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 RWE, 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 ($156K) sits 14% below the category median. Disclosed range: $125K to $188K.
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.
RWE AI Hiring
RWE has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in White Plains, NY, US. Compensation range: $188K - $188K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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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