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Responsibilities:
Noblis is seeking an AI Product Experience Architect IV to support our customer in Chantilly VA.
The AI Product Experience Architect will lead the coordinated product strategy, experience architecture, and workflow development necessary to achieve core AI platform functionality by applying deep expertise in human\-centered systems thinking, complex workflow orchestration, and behavioral understanding across highly interconnected entry and exit points. In this capacity, the incumbent leverages expert experience in product strategy, interaction design, innovation, and user psychology to guide stakeholders toward discovering and realizing their ideal future\-state workflows through intuitive, seamless, and highly adaptive user experiences that meet operational objectives at mission speed, drive enterprise application adoption, and deliver Section 508\-compliant, modern user experiences. The role is responsible for generating product demand by uncovering latent user problems, mapping complex investigative workflows, analyzing user/mission needs, and translating them into compelling, intuitive, and high\-impact design solutions. The ideal candidate must be an expert in transforming ambiguous ideas into clear, intuitive, and actionable product experiences channeling deep experience, while serving as a systems thinker skilled in designing end\-to\-end user journeys, information architecture, and interaction flows that feel effortless and self\-explanatory. Additionally, the position requires mastery in behavioral\-driven UX design, rapid prototyping, and iterative usability testing to refine and validate experience quality, alongside a proven ability to guide multidisciplinary design teams, manage experience delivery, and utilize specialized environmental constraints such as tactical Dark Theme UI architectures to optimize user cognitive mapping under high\-stress operational conditions and guarantee platform stickiness.
Key Responsibilities
- Drives coordinated product strategy, experience architecture, and workflow development to achieve core AI platform functionality, aligning design decisions with mission objectives and enterprise adoption goals.
- Designs end\-to\-end user journeys, information architecture, and interaction flows across highly interconnected entry and exit points, ensuring experiences feel effortless and self\-explanatory.
- Maps complex investigative workflows, uncovers latent user problems, and translates ambiguous requirements into clear, intuitive, and actionable product experiences.
- Applies deep expertise in user psychology, behavioral science, and cognitive load theory to design adaptive user experiences that optimize decision\-making under high\-stress operational conditions.
- Guides stakeholders toward discovering and realizing their ideal future\-state workflows through facilitated design thinking sessions, journey mapping, and collaborative visioning exercises.
- Leads rapid prototyping cycles and iterative usability testing to refine and validate experience quality, ensuring design solutions meet operational objectives at mission speed.
- Ensures all user experiences meet Section 508 accessibility standards while maintaining modern, high\-impact design quality across all platform touchpoints.
- Utilizes specialized environmental constraints, including tactical Dark Theme UI architectures, to optimize user cognitive mapping and guarantee platform stickiness in operational environments.
- Guides multidisciplinary design teams, manages experience delivery across sprints and Program Increments, and establishes design system governance and standards.
- Generates product demand by uncovering latent user problems, analyzing user/mission needs, and translating them into compelling, high\-impact design solutions that drive enterprise adoption.
Required Qualifications:
- US Citizenship is required.
- Active Top Secret (TS) clearance with eligibility for Sensitive Compartmented Information (SCI) and ability to obtain a Counterintelligence (CI) Polygraph.
- Bachelor's or Master's degree in Human\-Computer Interaction (HCI), Cognitive Science, Interaction Design, Industrial Design, User Experience, or a related field.
- 10\+ years of progressive experience in product design, UX/UI design, or experience architecture, with at least 8 years leading product strategy and experience design for complex, mission\-critical systems and at least 3 years designing AI\-enabled or intelligent system interfaces.
- Must provide a comprehensive portfolio demonstrating mastery in end\-to\-end experience architecture, complex workflow design, and systems\-level interaction design for enterprise or mission\-critical platforms.
- Minimum of 10 years supporting product design or experience architecture within government agencies, intelligence community, federal contractors, or highly regulated public sector environments, with demonstrated experience across multiple programs or agencies.
- Demonstrated mastery in behavioral\-driven UX design, including applied knowledge of cognitive load theory, decision architecture, and user psychology in high\-stakes operational environments.
- Expert\-level knowledge of Section 508, WCAG 2\.1/2\.2 AA standards, and inclusive design practices with proven implementation across enterprise platforms.
- Mastery in rapid prototyping tools (such as Figma, Sketch, Axure, or equivalent) and iterative usability testing methodologies including moderated/unmoderated testing, A/B experimentation, and heuristic evaluation.
- Proven ability to guide multidisciplinary design teams of 5 or more, manage experience delivery across agile cadences, and establish design system governance.
Desired Qualifications:
- Active TS/SCI CI Poly
- Nielsen Norman Group UX Certification or equivalent professional credential.
- Certified Usability Analyst (CUA) or Certified User Experience Professional (CUXP).
- Experience designing interfaces for AI/ML systems including conversational AI, agentic workflows, explainable AI (XAI), or human\-in\-the\-loop decision systems.
- Expertise in Dark Theme UI architecture, OLED\-optimized interfaces, or tactical/operational display design for command\-and\-control environments.
- Experience with design systems at scale (such as atomic design methodology, component libraries, and design tokens).
- Background in cognitive task analysis (CTA), ecological interface design, or situation awareness frameworks.
- Published research or patents in human\-AI interaction, adaptive interfaces, or intelligent user experience design.
- Experience with eye\-tracking, biometric usability testing, or neuroergonomic evaluation methods.
- SAFe Product Owner/Product Manager (POPM) or equivalent Agile product certification.
- Prior experience as a trusted design advisor to agency CIOs, CTOs, or Chief Experience Officers.
Overview:
Overview
Noblis and our wholly owned subsidiaries, Noblis ESI and Noblis MSD, take on some of the nation’s toughest challenges, delivering advanced solutions to our customers’ most critical missions. We bring together leading scientific, engineering, and management expertise in a culture grounded in objectivity and collaboration, ensuring our work creates lasting impact across federal missions.
We work with a broad range of government agencies in the defense, intelligence, and federal civilian sectors. Learn more and find opportunities at careers.noblis.org Why Work at Noblis
At Noblis, we share a passion for excellence and innovation, and we create an environment where people can do meaningful work while maintaining the balance that keeps them energized and fulfilled. We seek out individuals with a natural curiosity and desire to collaborate and learn. We believe our people are our greatest strength, and we consistently seek exceptionally skilled, mission‑driven professionals who care deeply about doing work that enriches lives and makes our nation safer.
Noblis has earned numerous workplace awards for our culture, our commitment to employee well‑being, and our dedication to meaningful, impactful work. We also maintain a drug‑free workplace. *Remote/hybrid status is subject to change based on Noblis and/or government requirements.*
Commitment to Non\-Discrimination:
All qualified applicants will receive consideration for employment without regard to race, color, ethnicity, sex, age, national origin, religion, physical or mental disability, pregnancy/childbirth and related medical conditions, veteran or military status, or any other characteristics protected by applicable federal, state, or local law.
If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact us.
EEO is the Law \| E\-Verify \| Right to Work
Total Rewards:
At Noblis we recognize and reward your contributions, provide you with growth opportunities, and support your total well\-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, and work\-life programs. Our award programs acknowledge employees for exceptional performance and superior demonstration of our service standards. Full\-time and part\-time employees working at least 20 hours a week on a regular basis are eligible to participate in our benefit programs. Other offerings may be provided for employees not within this category. We encourage you to learn more about our total benefits by visiting the Benefits page on our Careers site.
Compensation at Noblis is determined by various factors, including but not limited to, the combination of education, certifications, knowledge, skills, competencies, and experience, internal and external equity, location, clearance level, as well as contract\-specific affordability, organizational requirements and applicable employment laws. The projected compensation range for this position is based on full time status. For part time or on\-call staff, compensation is proportionately adjusted based on hours worked. While monetary compensation is important, it's just one component of Noblis’ total compensation package.
Posted Salary Range: USD $160,800\.00 \- USD $251,325\.00 /Yr.
Salary Context
This $160K-$251K 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 Noblis, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $160K to $251K.
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.
Noblis AI Hiring
Noblis has 4 open AI roles right now. They're hiring across AI/ML Engineer. Based in Chantilly, VA, US. Compensation range: $207K - $251K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 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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