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COMPANY OVERVIEW
Join our award\-winning team at Information Management Resources, Inc. (IMRI), a small business leader in the technology industry known for our commitment to innovation, excellence, and authenticity. Founded in 1992, IMRI has been at the forefront of delivering advanced cybersecurity and IT solutions, safeguarding organizations against evolving threats. We have built a reputation for our expertise in Cybersecurity, Digital Transformation, Strategic Business Consulting, and Staff Augmentation. Guided by our core values of innovation, excellence, and a solution\-driven mindset, we have served a diverse portfolio of customers that includes federal agencies, state and local governments, and Fortune 1000 companies.
At IMRI, we recognize the integral part our employees play in our ongoing success. To support this, we offer a comprehensive benefits package, tailored to meet the individual needs of our employees. We are committed to promoting their overall well\-being and equipping them with the necessary tools to flourish in their careers. We welcome you to be a part of our ongoing mission as we continue to navigate the digital landscape, committed to empowering organizations with our innovative solutions.
Position: Senior IT Program Manager – Federal AI Technology Program
Our organization is seeking an experienced Senior IT Program Manager to lead the deployment, operations, and adoption growth of an AI technology solution for a federal government client. This program includes pilot implementation, nationwide rollout, workflow integration, training, service desk support, cybersecurity monitoring, and compliance reporting.
The Senior IT Program Manager will serve as the single point of accountability for program delivery, client engagement, team performance, and contract profitability. The Senior IT Program Manager will also lead executive stakeholder engagement, customer adoption, and financial performance. This role requires experience leading federal IT programs, managing profit and loss, and supporting secure operational environments such as corrections, detention, law enforcement, or public safety.
Key Responsibilities:
- Lead the full program lifecycle, from pilot deployment through enterprise\-wide implementation and steady\-state operations.
- Manage program budget, cost control, forecasting, profit and loss, and executive reporting.
- Serve as the primary contact for federal stakeholders, contracting officers, COR/COTR representatives, and client leadership.
- Lead business process analysis, workflow integration, training, onboarding, service desk operations, user support, and customer adoption.
- Coordinate cybersecurity monitoring, compliance, audit readiness, and secure deployment across approved environments.
- Manage milestones, risks, issues, change control, deliverables, and performance reporting.
- Build KPI dashboards measuring customer adoption, utilization, service levels, operational performance, compliance, and return on investments (ROI).
- Lead implementation, training, service desk, cybersecurity, and compliance team members.
- Identify opportunities to expand the program to additional facilities, agency components, or related AI\-enabled use cases.
- Ensure compliance with federal acquisition, data governance, cybersecurity, and contract requirements.
- Travel nationwide during deployment and implementation activities (approximately 25% of time)
Required Qualifications:
- 15\+ years of IT program or project management experience, including large\-scale implementation and operations programs.
- Experience supporting federal government contracts as a consultant or contractor.
- Experience in corrections, detention, law enforcement, public safety, or similar mission\-critical environments.
- Proven experience managing program budgets, profitability, forecasting, and profit and loss responsibility.
- Experience with federal contract vehicles such as GSA MAS, GWACs, IDIQs, or OTAs.
- Ability to lead cross\-functional teams across technology, training, service desk, cybersecurity, compliance, and operations.
- Strong program governance skills, including risk management, milestone tracking, change control, reporting, and deliverables management.
- Excellent communication skills with experience briefing senior and executive level management, government officials, or board of directors.
- Working knowledge of secure government IT environments, cloud deployments, cybersecurity, and compliance requirements.
- Bachelor’s degree in information technology, Business Administration, Public Administration, Criminal Justice, or related field.
- Active DoD Top Secret clearance or eligibility for a Top\-Secret clearance required.
Preferred Qualifications:
- Experience supporting DHS or comparable federal public safety agencies.
- PMP, PgMP, or equivalent certification.
- Experience implementing AI\-enabled solutions an exceptional plus \- language access, translation, or transcription technologies.
- Experience establishing or scaling service desk operations.
IMRI offers top\-tier benefits that include: medical coverage through nationally recognized carriers, ancillary coverages, paid vacation and sick leave in compliance with all state and local laws, 401(k) with company match, company paid life insurance and LTD, and several additional voluntary coverages.
Pay will be commensurate with the experience, skills, and qualifications that the candidate brings to the position.
Equal Employment Opportunity Statement
*IMRI is an Equal Employment Opportunity employer. IMRI prohibits unlawful discrimination and harassment and provides equal employment opportunity to all applicants and employees consistent with applicable federal, state, and local laws. Employment decisions are based on qualifications, merit, business needs, and other lawful job\-related factors without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, genetic information, or any other characteristic protected by law. As a federal contractor, IMRI complies with Section 503 of the Rehabilitation Act and VEVRAA and takes affirmative action with respect to qualified individuals with disabilities and protected veterans as required by law.*
Salary Context
This $175K-$225K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At IMRI Technology & Engineering Solutions, 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 in Demand for This Role
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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($200K) sits 9% below the category median. Disclosed range: $175K to $225K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
IMRI Technology & Engineering Solutions AI Hiring
IMRI Technology & Engineering Solutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $225K - $225K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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