Interested in this AI Architect role at Applied Research Solutions?
Apply Now →Skills & Technologies
About This Role
Applied Research Solutions is seeking a full-time Principal AI Architect for Hanscom AFB. The Principal AI Architect is a senior technical leader responsible for defining and guiding the architecture, engineering strategy, integration, and deployment of advanced artificial intelligence capabilities supporting U.S. Department of Defense (DoD) missions. This role requires employee pass background screening for SAP.
The Automated Classification Management Environment (ACME) is a program initiated by the Air Force to modernize the classification management system. The current manual classification infrastructure limits the Department of War's ability to share data efficiently, which is crucial for Joint All Domain Command and Control (JADC2) operations.
The ACME program aims to manage the lifecycle of classification and declassification in accordance with Executive Order 13526 and relevant policies, transitioning from a fragmented manual system to an AI-driven automated solution.
The ACME program will involve several key tasks:
- Transitioning from a manual classification framework to an AI-driven automated enterprise solution.
- Managing the lifecycle of classified national security information, including original classification, declassification, and releasability processes.
- Addressing challenges such as financial strain due to lack of interoperability, static guidance leading to errors, a backlog of records awaiting review, and high error rates in derivative classifications.
- Implementing machine-readable data infrastructure and AI tools for automation across various classification levels (Unclassified, CUI, Confidential, Secret, Top Secret, SCI).
- Engaging in agile development methodologies for rapid prototyping and integration of new capabilities.
This role provides enterprise-level technical leadership across AI/ML, generative AI, cloud, data, cybersecurity, software engineering, and mission systems. The Principal AI Architect translates complex mission requirements into secure, scalable, resilient, and interoperable AI architectures and establishes technical patterns that can be adopted across programs and operational environments.
The successful candidate will serve as a trusted technical advisor to government customers, senior program leadership, engineering organizations, and mission stakeholders, while helping establish the technical vision and roadmap for next-generation AI capabilities.
Why Work with us?
Applied Research Solutions (ARS) is respected as a world-class provider of technically integrated solutions as we deliver premier talent and technology across our focused markets for unparalleled, continuous mission support. Awarded a Best Places to Work nominee since 2020, ARS recognizes that without our career- driven, loyal professionals, we would not be able to deliver state-of-the-art results for our mission partners. We firmly believe that prioritizing our employees is of the upmost importance. We provide a culture where our employees are challenged to meet their career goals and aspirations, while still obtaining a work/life balance. ARS employees are motivated through our industry competitive benefits package, our awards and recognition program, and personalized attention from ARS Senior Managers.
Responsibilities Include:
AI Architecture & Technical Leadership
- Define enterprise and mission-level architectures for AI, machine learning, generative AI, and intelligent decision-support capabilities.
- Establish technical vision, architecture principles, reference architectures, design patterns, and technology roadmaps for DoD AI programs.
- Lead architecture decisions spanning AI models, data platforms, cloud infrastructure, applications, APIs, cybersecurity, networking, and edge computing.
- Evaluate emerging AI technologies and determine their applicability to operational and mission requirements.
- Provide technical leadership across the complete AI lifecycle - from experimentation and prototyping through production, deployment, and sustainment.
- Establish reusable architecture patterns that enable secure and scalable adoption of AI across multiple mission areas.
- Lead technical architecture reviews and provide recommendations to senior government and program leadership.
Generative AI & Advanced AI
- Architect enterprise-grade solutions leveraging large language models (LLMs), foundation models, multimodal AI, retrieval-augmented generation (RAG), AI agents, and domain-specific models.
- Design secure architectures for government use of commercial, open-source, and internally developed foundation models.
- Establish approaches for model selection, fine-tuning, prompt engineering, evaluation, model serving, inference optimization, and lifecycle management.
- Design AI agent architectures incorporating tools, APIs, knowledge bases, workflow orchestration, human oversight, and appropriate safeguards.
- Establish methodologies for evaluating model accuracy, robustness, security, reliability, bias, hallucination, and mission suitability.
- Develop architectures for AI-enabled decision support while maintaining appropriate human oversight and accountability.
Cloud, Edge & Mission Systems
- Design AI architectures across cloud, hybrid, on-premises, disconnected, tactical, and edge environments.
- Architect GPU/accelerated computing infrastructure for AI training and inference workloads.
- Develop strategies for deploying AI capabilities in constrained or intermittently connected operational environments.
- Integrate AI services with existing DoD applications, enterprise platforms, mission systems, data environments, and APIs.
- Define architectures supporting high availability, resilience, scalability, fault tolerance, and mission continuity.
AI Engineering & MLOps
- Establish enterprise MLOps and AI engineering practices supporting repeatable model development, testing, deployment, monitoring, and lifecycle management.
- Define CI/CD and DevSecOps patterns for AI/ML systems.
- Establish model registries, feature stores, data pipelines, evaluation frameworks, observability, and model monitoring architectures.
- Design automated mechanisms for model validation, security testing, performance monitoring, drift detection, and rollback.
- Ensure AI systems can be maintained, upgraded, and governed throughout their operational lifecycle.
Security, Compliance & Responsible AI
- Integrate cybersecurity requirements into AI architectures from initial design through deployment and sustainment.
- Apply Zero Trust principles to AI, data, application, identity, and infrastructure architectures.
- Support Risk Management Framework (RMF), Authority to Operate (ATO), security control implementation, continuous monitoring, and related federal/DoD processes.
- Design architectures addressing data protection, identity and access management, encryption, auditability, model security, supply-chain security, and secure software development.
- Establish controls for AI model integrity, data provenance, access control, prompt injection, data leakage, adversarial inputs, and other AI-specific security risks.
- Incorporate responsible AI principles, explainability, traceability, human oversight, and appropriate governance into system architecture.
- Partner with cybersecurity and compliance teams to ensure AI solutions satisfy applicable DoD and federal requirements.
Data Architecture
- Define architectures for collecting, integrating, managing, governing, and securing AI-ready data.
- Establish data strategies supporting structured, unstructured, geospatial, sensor, text, image, video, and other mission data.
- Design data pipelines and knowledge architectures supporting RAG, model training, analytics, and AI inference.
- Establish data governance, metadata, lineage, quality, access, and provenance requirements.
- Address data interoperability across enterprise, mission, coalition, and edge environments where applicable.
Technical Strategy & Stakeholder Leadership
- Act as the senior technical authority for AI architecture within assigned programs.
- Engage directly with senior government executives, Chief Architects, Chief Technology Officers, Chief Data/AI Officers, program managers, mission owners, and engineering leadership.
- Translate strategic mission objectives into executable technical architectures and implementation roadmaps.
- Lead technical working groups involving government personnel, contractors, vendors, and technology partners.
- Assess build-versus-buy decisions and evaluate commercial, government, and open-source AI technologies.
- Provide technical guidance for acquisition strategies, technical requirements, Statements of Work (SOWs), Requests for Proposals (RFPs), and vendor evaluations.
- Mentor senior engineers, architects, data scientists, and AI practitioners.
- Other duties as assigned.
Qualifications/ Technical Experience Requirements:
- Must be a US citizen
- Top Secret Security Clearance with SCI eligibility
- Must pass SAP Screening
- Bachelor's degree in computer science, Computer Engineering, Artificial Intelligence, Data Science, Systems Engineering or related technical discipline
- Master's degree in relevant technical discipline preferred
- 15+ years of experience in software engineering, systems engineering, cloud architecture, AI/ML, data architecture, or related fields
- 5+ years of experience designing and implementing enterprise-scale AI/ML solutions
- Demonstrated experience serving as a technical architect or senior technical leader for complex systems
- Extensive experience with AI/ML architectures and production AI systems
- Strong understanding of generative AI, LLMs, RAG, foundation models, model evaluation, and AI agents
- Strong understanding of distributed systems, cloud-native architectures, APIs, microservices, containers, and Kubernetes
- Extensive experience with MLOps, DevSecOps, CI/CD, and AI/ML lifecycle management
- Strong understanding of cybersecurity architecture and secure software development
- Demonstrated ability to communicate complex architecture and technology concepts to senior technical and government stakeholders
The expected annual salary range: $195k - $215k. Salary is dependent upon the role and associated responsibilities, candidate's experience, and qualifications to include education/training, and key skills.
All positions at Applied Research Solutions are subject to background investigations. Employment is contingent upon successful completion of a background investigation including criminal history and identity check.
This contractor and subcontractor shall abide by the requirements of 41 CFR 60-741.5(a). This regulation prohibits discrimination against qualified individuals on the basis of disability and requires affirmative action by covered prime contractors and subcontractors to employ and advance in employment qualified individuals with disabilities.
This contractor and subcontractor shall abide by the requirements of 41 CFR 60-300.5(a). This regulation prohibits discrimination against qualified protected veterans and requires affirmative action by covered contractors and subcontractors to employ and advance in employment qualified protected veterans.
Education
Required* Bachelors or better in Electrical Engineering or related field
Motivations
Preferred* Work-Life Balance: Inspired to perform well by having ample time to pursue work and interests outside of work
- Flexibility: Inspired to perform well when granted the ability to set your own schedule and goals
- Self-Starter: Inspired to perform without outside help
- Ability to Make an Impact: Inspired to perform well by the ability to contribute to the success of a project or the organization
- Goal Completion: Inspired to perform well by the completion of tasks
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
Salary Context
This $195K-$215K range is above the median for AI Architect roles in our dataset (median: $179K across 32 roles with salary data).
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 Applied Research Solutions, 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. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($205K) sits 11% below the category median. Disclosed range: $195K to $215K.
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.
Applied Research Solutions AI Hiring
Applied Research Solutions has 2 open AI roles right now. They're hiring across AI/ML Engineer, AI Architect. Positions span Beavercreek, OH, US, Bedford, MA, US. Compensation range: $215K - $215K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.