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About This Role
About NDi:
Network Designs, Inc. (NDi) is a leading Federal contractor that specializes in designing, developing, and delivering information technology and network solutions for government customers. Founded in 1985, NDi's firmly defined core values have driven all aspects of the business, which have been paramount to our company's success and the establishment of an enjoyable workplace atmosphere. At NDi, we believe that our people are the cornerstone of our success, and we value collaboration, career growth, and winning ideas. Military Veterans Encouraged to Apply.
Job Description:
We are seeking an Enterprise AI/ML Architect to define and govern enterprise AI/ML architecture, model lifecycle practices, and secure implementation patterns that turn high-value mission use cases into trustworthy, scalable production capabilities. This role supports the Enterprise InformationData Integration Program and works with cross-functional technical and mission teams to deliver secure, reliable, and well-documented outcomes.Requirements:
- U.S. Citizenship is required
- Must be able to obtain and maintain a Public Trust clearance
- This position is remote, candidate must reside in one of the following states: AL, AZ, DC, FL, GA, ID, MD, MS, NJ, NC, OK, OH, PA, SC, TN, TX, UT, VA, WV
- Occasional travel may be required. Candidates should be able to attend meetings at FAA facilities and other locations throughout the Continental United States (CONUS) as required.
- Must be available during Eastern Time (ET) business hours to support program needs and FAA coordination.
Qualifications and Experience:
- Master's degree, or approved equivalent, in data science, information technology, mathematics, statistics, or a related field
- Minimum 8 years of experience in computer science, engineering, or systems analysis, with a strong focus on AI and ML; at least 5 years of hands-on production programming with AI frameworks.
- Relevant experience must directly reflect work, tasks, and deliverables similar to those supported by this position.
- Strong written, verbal, analytical, organizational, problem-solving, and cross-functional collaboration skills.
- Ability to work with sensitive, confidential, or regulated information and follow applicable federal policies and procedures.
- Ability to use Government-issued accounts and designated collaboration and task-tracking systems as required.
Preferred Qualifications:
- Experience leading AI initiatives in aviation, government, finance, or another regulated environment.
- Production experience integrating sophisticated AI/ML services from AWS, Azure, or Google Cloud.
- Experience with LLMs, retrieval-augmented generation, model alignment, agentic workflows, aviation-safety data, or Palantir Foundry.
Responsibilities:
- Define target-state AI/ML architecture aligned with enterprise data architecture, security requirements, federal governance standards, and responsible-AI principles.
- Design secure ML pipelines, MLOps frameworks, feature stores, model registries, and lifecycle controls spanning development, validation, deployment, monitoring, retraining, and retirement.
- Establish architecture patterns for AI services, LLM and NLP capabilities, model integration, explainability, auditability, lineage, safety controls, and model governance.
- Lead identification and technical shaping of high-value AI use cases, needs analyses, MVPs, prototypes, pilots, and production implementations.
- Guide integration of AI capabilities into enterprise platforms, workflows, APIs, data pipelines, Palantir Foundry, and cloud AI services.
- Produce AI/ML architecture diagrams, solution-design artifacts, governance models, risk-review materials, technical standards, implementation plans, and value metrics.
- Support compatibility testing, deployment, operationalization, technical troubleshooting, knowledge transfer, workforce enablement, and measurable value demonstration.
- Advise and mentor architects, data scientists, ML engineers, developers, security practitioners, and program leaders while monitoring emerging AI technologies and regulations.
Compensation and Benefits:
At NDi, we value our team and are committed to retaining top talent by offering competitive benefits and compensation packages. Our employee benefits package includes comprehensive health, dental, vision, pet, and legal insurance. Our corporate benefits include 401(k) retirement matching, paid leave, paid holidays, and health and wellness programs. In addition, we provide employer-paid life and disability insurance, professional development, education benefits, and much more to ensure our team has the resources they need to thrive on and off the job.
Veterans First Commitment:
As a Service-Disabled Veteran-Owned Small Business (SDVOSB), NDi is dedicated to hiring veterans and providing a supportive work environment that honors their service while recognizing the unique skills and experiences they bring to our organization.
Our Commitment:
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law.
Apply Now: Take advantage of this unique opportunity to join one of the fastest-growing companies in Federal contracting!
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 9,653 AI roles we're tracking, AI Architect positions make up 1% of the market. At Network Designs, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $230,000 based on 212 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Network Designs AI Hiring
Network Designs has 1 open AI role right now. They're hiring across AI Architect. Based in McLean, VA, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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