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About This Role
As the recognized global standard for project\-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values\-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one\-of\-a\-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress.www.deltek.com
Business Summary
The Deltek Global Sales team has a passion for empowering project\-based businesses to achieve their goals. We relentlessly focus on our customers’ needs and strive to deliver an exceptional experience for all clients. If you are an enthusiastic, motivated professional who enjoys building and nurturing relationships – join our highly collaborative team to help power project success for our customers.
Position Responsibilities
This role serves as the technical engine behind our AI\-powered sales enablement strategy, driving innovation across our tech stack, accelerating seller productivity, and embedding AI into how we sell, learn, and engage.
You will act as a right hand to the Senior Manager of AI Enablement and a key partner to Sales, Marketing, Operations, and Partner teams bringing together tools, data, AI, and enablement into one cohesive, high\-impact system.
Deltek’s Sales Enablement organization is seeking a strategic and technically fluent AI \& Sales Technology leader to help design, build, and scale a best\-in\-class, AI\-powered sales ecosystem.
This individual will play a critical role in:* Embedding AI into seller workflows
- Driving adoption of our sales technology stack
- Enabling both internal sellers and external partners
- Translating complex technical capabilities into clear, actionable sales value
This is not a support role, this is a builder, architect, and accelerator role.
Key Responsibilities
AI Strategy \& Innovation* Partner with Enablement leadership to design and operationalize AI\-driven sales strategies
- Identify opportunities to embed AI into:
+ Prospecting
+ Deal qualification
+ Pipeline management
+ Content delivery
+ Coaching \& training
- Contribute to enterprise\-wide AI initiatives aligned to Deltek’s broader strategy
Sales Technology \& Systems Optimization* Act as a subject matter expert (SME) across the sales tech stack, including:
+ Salesforce (CRM, reporting, workflows)
+ Salesloft (cadence execution, call intelligence)
+ LinkedIn Sales Navigator (social selling strategies)
+ Allego (learning, content, coaching)
+ ZoomInfo, Terminus, Owler (data \+ intent platforms)
+ Eloqua / marketing automation tools
- Drive tool integration along with our tool strategist, optimization, and user experience improvements
- Evaluate and recommend new technologies that enhance seller productivity
AI Enablement \& Adoption* Build and deliver AI\-focused enablement programs (101 to advanced use cases)
- Design scalable frameworks for:
+ Prompt engineering
+ AI\-assisted selling motions
+ Workflow automation
- Lead initiatives such as:
+ AI “Prompt of the Week”
+ AI Power Hours / training sessions
+ AI certification programs
Partner Enablement \& Technical Messaging* Collaborate with Partner teams to:
+ Enable partners on Deltek’s AI capabilities and tools
+ Ensure consistent, high\-quality technical messaging externally
- Translate technical capabilities into business value narratives
- Support partner\-facing demos, use cases, and solution positioning
Program Execution \& Cross\-Functional Leadership* Act as a right hand to the Senior Manager, AI Enablement
- Partner closely with:
+ Sales Leadership
+ Marketing \& Product Marketing
+ Sales Operations
+ IT / Data teams
- Support rollout of strategic initiatives including:
+ AI\-powered playbooks (e.g., Playbook Pro)
+ Sales Council insights integration
+ Global onboarding and continuous learning programs
Analytics, Insights \& Continuous Improvement* Leverage data to:
+ Measure adoption and effectiveness of AI tools
+ Track impact on pipeline, deal velocity, and win rates
- Build dashboards and insights to inform:
+ Leadership decisions
+ Ongoing optimization of tools and programs
Qualifications
Required Qualifications* 7–10\+ years in Sales Enablement, Sales Operations, Revenue Operations, or Sales Technology roles
- Proven experience working with sales tech stacks and CRM systems (Salesforce required)
- Strong understanding of AI applications in sales, enablement, or GTM environments
- Experience building and delivering technical training or enablement programs
- Ability to translate complex technical concepts into simple, actionable insights
- Strong cross\-functional collaboration and stakeholder management skills
Preferred Qualifications* Experience with tools such as:
+ Salesforce, Salesloft, LinkedIn Sales Navigator, Allego
+ ZoomInfo, Terminus, Eloqua, Owler
- Familiarity with:
+ Prompt engineering and generative AI tools (e.g., ChatGPT, Claude)
+ AI\-driven sales workflows and automation
- Background in UX analysis / user experience optimization for sales tools
- Experience supporting partner ecosystems or channel enablement
- Exposure to data visualization tools (Tableau, Power BI, etc.)
What Success Looks Like* AI is embedded into daily seller workflows—not optional, but essential
- Increased:
+ Pipeline generation
+ Deal velocity
+ Seller productivity
- High adoption and satisfaction across the sales tech stack
- Partners confidently delivering technical and AI\-driven value stories
- Enablement recognized as a strategic driver of revenue impact
Why This Role Matters
This role sits at the intersection of AI, sales, and enablement transformation.
You will directly shape how our sellers operate, how our partners engage, and how we scale for the future.
Compensation Info
The U.S. salary range for this position is $93,000\.00\-$163,000\.00\. This range is subject to change as Deltek takes a number of factors into consideration when determining individual base pay, such as location, job\-related knowledge, skills and experience. Certain roles are eligible for additional rewards, including incentive compensation and equity.
Benefits and perks listed here may vary depending on the nature of employment with Deltek. Employees have access to healthcare benefits, a 401(k) plan and company match, paid vacation time and holidays, well\-living programs, short\-term and long\-term disability coverage, basic life insurance and tuition reimbursement.
Position Type
FT
Travel Requirements
20%
Compliance Requirements
Certain roles may have additional privacy, security and compliance requirements to the extent they support Costpoint GCCM or similar product offerings.
EEO Statement
*Deltek, Inc. is an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.*
E\-Verify Statement
Deltek, Inc., utilizes the E\-Verify program with every potential new hire. This makes it possible for us to make certain that every employee who works for Deltek is eligible to work in the United States. To learn more about E\-Verify you can call 1\-800\-255\-7688 or visit their website by clicking the logo below. E\-Verify® is a registered trademark of the United States Department of Homeland Security.
Applicant Privacy Notice
*Deltek is committed to the protection and promotion of your privacy. In connection with your application for employment with us at Deltek, it is necessary for us to collect, store and use information about you (“Personal Data”) to administer and evaluate your application. We are the “controller” of the Personal Data you provide us and will process any such Personal Data in accordance with applicable law and the statements contained in this* Employment Candidate Privacy Notice*. Additionally, we have not sold and do not sell Personal Data you provide to us through the job application process.*
Salary Context
This $93K-$163K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Deltek, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($128K) sits 23% below the category median. Disclosed range: $93K to $163K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Deltek AI Hiring
Deltek has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $163K - $180K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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