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About This Role
Amentum is seeking a Strategic Assessment Analyst (AI \& Data Systems) to provide operational planning, data integration, research, and analysis support to the US PACOM J5 Strategy Branch. This position serves as a critical member of the J5 Assessment Team, acting as the hub for assessment efforts among the directorates and our components.
The Strategic Assessment Analyst will support the J5 Strategy Branch by leveraging artificial intelligence, quantitative data modeling, and qualitative analysis to assess operational plans, programs, and strategic policies.
Primary Roles and Responsibilities:
- Design, implement, and utilize Maven Smart System tools and agents to streamline and enhance operational and strategic assessment workflows.
- Provide process methodology and analysis to execute comprehensive assessment functions, merging both quantitative and qualitative methodologies.
- Engineer and maintain cross\-domain data processes, ensuring that disparate data sources from various directorates and components are ingested, fused, and analyzed effectively.
- Provide robust Knowledge Management solutions in the context of AI models, tools, and agents—specifically focusing on Maven Smart Systems—to ensure assessment data is accessible, reliable, and actionable.
- Construct and deliver analytical products for use by the PACOM Commander and other senior leaders.
- Develop automated dashboards, briefing documents, and decision papers on various topics to support senior leadership decision\-making regarding recent, ongoing, or anticipated military activities.
- Assist with the production and implementation of long\-term, fully integrated Department of War (DoW) strategies by applying innovative AI approaches to campaign and contingency plan assessments.
Minimum Requirements:
- Bachelor’s degree in data science, Operations Research, Information Technology, Systems Engineering, Applied Economics, National Security Studies, or related field.
- Familiarity with military assessment processes, demonstrating proficiency in both quantitative and qualitative assessment design.
- Proven ability to design, deploy, and use Maven Smart System tools and agents in a secure environment.
- Demonstrated ability to use AI capabilities (e.g., large language models, machine learning algorithms, automated agents) to execute complex assessment functions.
- Experience in engineering cross\-domain data processes, with an understanding of data pipelines, architecture, and secure knowledge management principles.
- At least 5 years’ experience working in military operations, either on an operations staff, in strategic planning, or within an intelligence/data fusion role.
- Demonstrate excellent written and oral communications, with the ability to translate complex AI/data\-centric findings into digestible strategic military advice.
- Must have an active Top\-Secret clearance, with TS/SCI eligibility later during employment. Note: US Citizenship is required to obtain Top\-Secret Clearance.
- This position may require a polygraph after employment.
Preferred Qualifications:
- Master’s degree in operations research, Data Analytics, or a related technical discipline.
- At least 3 years’ experience on a senior military staff (Service HQ, Major Command, Office of the Secretary of Defense, or the Joint Staff) specifically working within the Joint Planning Process (JPP).
- Advanced proficiency in programming languages commonly used in data analysis and AI (e.g., Python, R, SQL).
- Previous experience supporting a J5 Directorate or military strategy branch.
Compensation \& Benefits
HIRING SALARY RANGE: $135K \- $160K (Salary to be determined by the education, experience, knowledge, skills, and abilities of the applicant internal equity, and alignment with market data.)
This position includes a competitive benefits package. For more detailed information on our Benefits and what it is like to work for Amentum: please visit our careers site: www.amentumcareers.com
Compensation Details:
$135K \- $160K
The compensation range or hourly rate listed for this position is provided as a good\-faith estimate of what the company intends to offer for this role at the time this posting was issued. Actual compensation may vary based on factors such as job responsibilities, education, experience, skills, internal equity, market data, applicable collective bargaining agreements, and relevant laws.
Benefits Overview:
Our health and welfare benefits are designed to support you and your priorities. Offerings include:
- Health, dental, and vision insurance
- Paid time off and holidays
- Retirement benefits (including 401(k) matching)
- Educational reimbursement
- Parental leave
- Employee stock purchase plan
- Tax\-saving options
- Disability and life insurance
- Pet insurance
*Note: Benefits may vary based on employment type, location, and applicable agreements. Positions governed by a Collective Bargaining Agreement (CBA), the McNamara\-O'Hara Service Contract Act (SCA), or other employment contracts may include different provisions/benefits.*
Original Posting:
07/16/2026 \- Until Filled
Amentum anticipates this job requisition will remain open for at least three days, with a closing date no earlier than three days after the original posting. This timeline may change based on business needs.
Amentum is proud to be an Equal Opportunity Employer. Our hiring practices provide equal opportunity for employment without regard to race, sex, sexual orientation, pregnancy (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, ancestry, United States military or veteran status, color, religion, creed, marital or domestic partner status, medical condition, genetic information, national origin, citizenship status, low\-income status, or mental or physical disability so long as the essential functions of the job can be performed with or without reasonable accommodation, or any other protected category under federal, state, or local law. Learn more about your rights under Federal laws and supplemental language at Labor Laws Posters.
Salary Context
This $135K-$160K range is below 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 Amentum, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($147K) sits 33% below the category median. Disclosed range: $135K to $160K.
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.
Amentum AI Hiring
Amentum has 6 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Camp H M Smith, HI, US, Linthicum, MD, US, Fort Meade, MD, US. Compensation range: $160K - $255K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 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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