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About This Role
AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
*We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.*
AHEAD builds AI\-powered platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of AI digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
As a ServiceNow Principal Technical Consultant with a focus on AI and agentic capabilities, you will utilize your ServiceNow expertise and experience to architect, design, develop, and deploy AI\-powered solutions on the ServiceNow platform — including Now Assist, AI Agents, Agentic AI Workflows, Predictive Intelligence, and GenAI\-enabled process automation. You will drive a collaborative team leading, mentoring, and ensuring development efforts are well documented and delivered with quality, owning the overall outcome of your projects. The ServiceNow Principal Technical Consultant is an experienced subject matter expert and focuses on development and delivery of value\-added integration and consultative services in the area of Enterprise AI solutions, designing, deploying, and integrating various product sets — with an emphasis on driving measurable business outcomes through intelligent automation. There is an expectation of at least 25% travel.
### Roles \& Responsibilities
- Lead project teams to deploy AI and agentic solutions on the ServiceNow platform, including Now Assist, AI Agents, AI Control Tower and AI Agent Orchestration
- Lead complex programs of multiple resources delivering AI\-enabled ITSM, ITOM, CMDB/CSDM, HRSD, CSM, SecOps, and ITAM capabilities
- Lead the architecture and design of complex AI/agentic solutions, including prompt design, skill configuration, and workflow orchestration across ServiceNow AI Experience
- Lead the creation of written deliverables, including AI adoption roadmaps, use case business cases, and governance frameworks
- Lead client demos and working sessions showcasing GenAI and agentic capabilities
- Lead integration design sessions connecting ServiceNow AI capabilities with third\-party LLMs, data sources, and enterprise systems
- Lead client workshops as process, technical, and AI strategy expert
- Serve as escalation point for project team on AI/agentic delivery matters
- Work to influence team members, broader internal team, and external customers, likely including senior management, to agree and accept new AI\-driven concepts, practices, and approaches
- Obtain and maintain certifications with associated qualifications, including ServiceNow AI\-focused credentials (e.g., Now Assist, Certified Application Developer with AI specialization)
- Maintain expert\-level certifications and stay current on ServiceNow's evolving AI/agentic product roadmap
- Identify and communicate AI\-driven opportunities across the client portfolio
- Participate in pre\-sales cycle as AI/agentic technical expert, scoping and positioning AI use cases
- Provide thought leadership to AHEAD and our customers on AI adoption, governance, and ROI within ServiceNow
- Communicate with external customers, which may include top management, on matters that require explanation, interpretation, and/or advising regarding AI capabilities and risk
- Craft innovative and high\-impact AI solutions for complex client programs, relying on large teams to implement
- Contribute to projects/programs that may address future AI concepts, products, and technologies on the ServiceNow platform
- Drive consensus with customers in solving complex AI/agentic solution design challenges
- Establish and advise on AI governance, responsible AI use, data privacy, and model performance monitoring within ServiceNow deployments
### Qualifications
- Subject matter expert on the ServiceNow platform with demonstrated expertise in AI and agentic capabilities (Now Assist, AI Agents, Predictive Intelligence, Virtual Agent/NLU preferred)
- Expert knowledge on at least two process areas within the ServiceNow platform, with applied AI/automation experience in at least one
- Expert\-level development skills on the ServiceNow platform, including scripting for AI Agent configuration, skill building, and workflow orchestration
- Recognized expertise in AI/agentic solution design within the organization
- Demonstrate deep expertise across multiple technologies, including GenAI/LLM concepts, prompt engineering, and AI governance frameworks
- Able to articulate trade\-offs between architecture approaches, including build\-vs\-configure decisions for AI capabilities and model/tooling selection
- Strong skills integrating ServiceNow AI capabilities with third\-party tools, LLMs, and data platforms
- Strong presentation skills, particularly in communicating AI value and ROI to technical and executive audiences
- Strong project and situational awareness
- Strong communication skills
- Strong attention to detail
- Self\-starter with a demonstrated interest in staying ahead of ServiceNow's AI/agentic product evolution
- Able to travel as needed, up to 15%
### Expectations
- A lead contributor to their team and the organization as a whole, driving AI/agentic adoption
- Bring thought leadership to our organization and our customers on AI within ServiceNow
- Contribute to projects/programs that may address future AI concepts, products, and technologies
- Coordinate cross\-practice and contribute to cross\-practice deliverables; help draft AI adoption standards and playbooks
- Lead multiple resources when on a cross\-practice AI/agentic project
- Be an early adopter of new AI\-related certifications
- Utilized by pre\-sales for AI opportunity identification, scoping, and positioning of services and products, including opportunities across practices, and engage pre\-sales to begin new AI\-focused campaigns that cross practices
- Primary contributor to complex workshops that span multiple practice areas inside of AHEAD, with a focus on AI use case discovery
- Be able to provide advanced data or situational analysis that requires the evaluation of intangibles, including AI readiness and change management considerations
- Drive scoping, planning, and methodology for critical AI/agentic projects
- Work on impactful and unique issues at the frontier of ServiceNow's AI capabilities
*The compensation range indicated in this posting reflects the On\-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount. This OTE range may vary based on the candidate’s relevant experience, qualifications, and geographic location.*
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top\-notch technologies in a multi\-million\-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
USA Employment Benefits include:
- Medical, Dental, and Vision Insurance
- 401(k)
- Paid company holidays
- Paid time off
- Paid parental and caregiver leave
- Plus more! See benefits https://www.aheadbenefits.com/ for additional details.
Use of AI:
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, assessing responses, or to capture recordings and create transcriptions or summaries during interviews. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please refer to the Candidate Privacy Notice or contact us at [email protected].
You may opt\-out of the review or analysis of your application and resume by AI tools by using the General Application. Please include the role you wish to apply for in the Additional Information field. You may also choose to opt\-out of recording and transcription at any time, including after joining an interview. Candidates will not be penalized for choosing to opt\-out.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $180K-$200K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Ahead, 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 $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($190K) sits 12% below the category median. Disclosed range: $180K to $200K.
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.
Ahead AI Hiring
Ahead has 8 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Remote, US, US. Compensation range: $150K - $300K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% 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 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).
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 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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