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Description
Position Summary
Precise Software Solutions Inc. is seeking an AI Project / Program Manager to lead delivery of an enterprise Generative AI engineering program supporting the federal government. You will be the primary day-to-day point of contact for the Government POC, and you will be accountable for schedule, staffing, quality, risk, labor-hour stewardship, and reporting across the full AI system lifecycle.
You will turn a multidisciplinary AI engineering team into predictable, transparent delivery - running Agile cadence, governance checkpoints, and monthly program reviews - while making sure every deliverable is on time, accepted, and audit-ready.
- Must be a U.S. citizen or lawful permanent resident (green card holder).
- Must reside in the Washington, DC metropolitan area and be able to work on-site at DC Government offices.
- A Government background investigation is required; you must be able to obtain and maintain it.
Key Responsibilities
Program Leadership and Contract Management
- Serve as the contract/program manager (or designated alternate) with authority to act on daily operational matters, and as the primary liaison to the federal customer POC and customer leadership.
- Evaluate proposed AI system changes with the Government, providing options, recommendations, level-of-effort and schedule estimates, and implementation impacts.
- Keep contract performance aligned with the Performance Work Statement and the Quality Assurance Surveillance Plan performance standards; route scope changes to the federal customer POC.
Planning, Schedule, and Agile Delivery
- Develop and maintain the Task Order Management Plan with the Lead AI Engineer, including the resource-loaded schedule, staffing plan, milestones, dependencies, and governance checkpoints; re-baseline after any priority change.
- Run the two-week Agile cadence with the technical leads, including sprint retrospectives, burn-up charts, and velocity tracking.
- Maintain project plans, schedules, decision logs, action-item logs, and requirements traceability in Government-approved tools (e.g., Jira, Confluence, SharePoint).
Reporting and Communications
- Deliver weekly task execution reports and Monthly Progress Reports covering accomplishments, risks, deliverable status, labor usage, burn rate, AI operational metrics, and helpdesk trends.
- Develop and maintain the Communications Plan; lead weekly status meetings, Monthly Program Reviews, and risk reviews; and distribute meeting notes and action items.
- Respond to Government data calls and support customer AI use-case inventory and enterprise architecture reporting.
Risk, Quality, and Compliance
- Maintain the program risk register - including AI-specific risks such as model drift, data quality, model or API deprecation, and security - with owners, triggers, mitigations, and dated contingencies.
- Own the Quality Control Plan and deliverable quality process so that deliverables are accepted.
- Track compliance items such as mandatory training completion, background investigations, and Section 508 conformance on releases.
Staffing, Labor Hours, and Resources
- Manage staffing plans, onboarding, cross-training, backfills, and turnover; and maintain personnel reports, escalation contacts, and access lists.
- Track labor-hour consumption and burn rate by labor category against the funded ceiling, forecast estimate-at-completion, and give advance warning of potential funding shortfalls.
- Maintain the Government-furnished equipment inventory, and identify required software, cloud AI services, and equipment for Government provisioning.
- Ensure helpdesk coverage and service-level compliance reporting, including coverage during planned absences.
Deliverables You Will Own
- Quality Control Plan; Monthly Progress Reports; weekly Task Execution Reports; Help Desk / Support Summary Reports; Risk Register; Communications Plan; AI Use-Case Inventory updates; and Data Call Responses.
Requirements
- Bachelor's degree in Engineering, Computer Science, Systems, Business, or a related scientific/technical discipline and 12+ years of relevant experience.
- 8+ years of experience managing federal IT professional services projects or programs, including life-cycle, budget, cost, schedule, and performance tracking.
- Demonstrated experience managing Agile software delivery teams, including backlog management, sprint cadence, and release planning.
- Experience managing labor-hour or time-and-materials contracts, including burn-rate tracking, funding forecasts, and ceiling management.
- 2+ years of experience managing AI, machine learning, data, or cloud modernization projects.
- Working knowledge of federal IT security and compliance requirements (FISMA, NIST SP 800-53, FedRAMP, ATO) and Section 508.
- Strong written and verbal communication skills, including briefing Government executives and producing clear, accurate program reports.
- Project management certification: PMP (SAFe or CSM preferred in addition).
- Must be a U.S. citizen or lawful permanent resident (green card holder).
- Must reside in the Washington, DC metropolitan area and be able to work on-site at Government offices.
- A Government background investigation is required; you must be able to obtain and maintain it.
Preferred Qualifications
- Master's degree in Business, Engineering, Information Systems, or a related field.
- Experience supporting the federal government.
- Familiarity with Responsible AI governance, including the NIST AI RMF and OMB M-25-21 / M-25-22.
- Experience with CMMI (Level 3) or ISO 9001 / 20000 / 27001 quality processes.
- Proficiency with Jira, Confluence, SharePoint, and program management / portfolio tools; experience with earned value or estimate-at-completion methods.
- An active federal background investigation.
ABOUT US
Precise Software Solutions, Inc. is a mission-focused technology services company delivering secure digital platforms, infrastructure, and operational IT services to government organizations. A CMMI Level 3–appraised company, Precise partners with agency technology leaders and solution providers to design, build, operate, and modernize enterprise IT solutions that support critical public missions combining agility, innovation, and performance to deliver measurable results.
Precise specializes in cloud and hybrid infrastructure, platform engineering, security operations and compliance, application modernization, and data platforms and analytics. The company is known for its agile, delivery-driven approach and innovative engineering practices, applying operational rigor and performance-focused execution to improve system resilience, security, and scalability across complex government environments.
BENEFITS AND PERKS:
- Comprehensive Health Benefits (Medical, Dental and Vision)
- Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
- Retirement Plan with 4% match and discretionary match at year end
- Paid Time Off (PTO): 15 days of PTO accrued per year; 7 holidays+ 3 Floating holidays; 2 Innovation days (paid training days)
- Short Term and Long-Term Disability
- Paid Parental Leave
- Paid Jury Duty leave
- Life and AD&D Insurance
- Critical Illness Insurance
- Training and Development
- Wellness Incentives & Discount programs
- Employee Referral Program
- Annual Charity Donation Match
- Awards and Recognition
Equal Employment Opportunity Statement
Precise Software Solutions is committed to providing a workplace free from discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, age, national origin, disability, sexual orientation, gender identity or expression, marital status, genetic information, protected veteran status, or other legally protected status.
We are an inclusive organization and actively promote equality of opportunity for all with the right mix of talent, skills and potential. We expect every member of the Precise community to do their part to cultivate and maintain an environment where everyone has the opportunity to feel included and is afforded the respect and dignity they deserve.
Pay: $160,000.00 - $167,000.00 per year
Work Location: Hybrid remote in Washington, DC 20210
Salary Context
This $160K-$167K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Precise Software Solutions, Inc., 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($163K) sits 23% below the category median. Disclosed range: $160K to $167K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Precise Software Solutions, Inc. AI Hiring
Precise Software Solutions, Inc. has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Washington, DC, US. Compensation range: $167K - $167K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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