Lead AI Engineer, Architect

Precise Software Solutions, Inc.

. Serve as Senior Forward Deployed Engineer and enterprise-wide technical authority for the Government's Enterprise AI Solution Delivery and Support Services program .

Posted 10/9/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI solution architecture, integration, and deployment, with a strong focus on security frameworks and compliance. Proven ability to lead technical teams and deliver enterprise AI solutions in regulated environments.

Highest-signal resume keywords

AI Solution ArchitectureGenerative AI IntegrationMLOps PracticesAI Security FrameworksCloud AI Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML EngineeringEnterprise ArchitectureData EngineeringModel EvaluationAPIsData PipelinesZero Trust SecurityAdversarial TestingAI OrchestrationCloud Engineering

Soft Skills

LeadershipMentoringCommunicationTechnical Decision-MakingStakeholder Engagement

Tools & Technologies

AWS Generative AI/MLMicrosoft Azure AIGoogle CloudDatabricksKubernetesVector DatabasesOpen-Weight Model ServingFedRAMPNIST AI RMFOWASP Top 10

Certifications & Qualifications

Microsoft Azure AIAWS Generative AI/MLGoogle CloudDatabricks Generative AI EngineerSnowflake SnowProNVIDIA Generative AICertified Artificial Intelligence Practitioner

Industry Keywords

Responsible AIAI GovernanceFederal ComplianceSection 508WCAG 2.1FISMA ModerateAI Incident Response PlanTechnical OversightTask Order ManagementAgile Program Delivery

Tech Stack

Tools & technologies

AWSAzureCloudKubernetes

About the role

Key responsibilities & impact

Serve as Senior Forward Deployed Engineer and enterprise-wide technical authority for the Government's Enterprise AI Solution Delivery and Support Services program
Lead AI solution architecture, design, integration, deployment, and technical oversight for Generative AI, LLM, RAG, agentic, and AI-enabled automation capabilities
Architect agentic and multi-agent AI workflows and full-stack Model Context Protocol (MCP)-based components
Apply the Government's AI agent security framework, including OWASP Top 10 for LLM Applications and NIST AI RMF, with appropriate autonomy limits and human oversight
Define engineering standards, reusable architecture patterns, and delivery approaches across supported agencies
Document major architecture decisions for Government approval, including cloud AI platform design, data flows, integrations, encryption, access controls, fallback procedures, and technical debt
Provide hands-on leadership in development, integration, testing, deployment, troubleshooting, technical reviews, and release readiness
Ensure designs use Government-furnished tools and environments or open, standards-based technologies
Prepare Model/Service Approval Requests before integrating models or AI services
Lead the Authority to Operate (ATO) effort under the NIST Risk Management Framework (SP 800-37)
Manage security boundaries, FISMA Moderate categorization, ATO documentation, package submission, and maintenance of a current ATO or Interim ATO
Oversee AI-specific security, including prompt-injection, jailbreak, and data-poisoning defenses, red teaming, Zero Trust architecture, and the AI Incident Response Plan
Oversee AI data architecture, model evaluation, MLOps, and operational readiness
Monitor drift, retrieval quality, and security/compliance telemetry
Lead Responsible AI activities, including RAIAs, model cards, bias and fairness reviews, explainability documentation, and human-in-the-loop controls
Conduct quarterly AI governance reviews with customer stakeholders
Serve as a Tier 3 escalation resource for production issues, including after-hours escalation of critical incidents
Own the Task Order Management Plan, AI System Architecture Design Documents, AI Governance & Responsible AI Reports, RAIA packages, AI Incident Response Plan, and weekly AI efficiency and cost-savings metrics
Mentor engineers, oversee code and prompt reviews, and personally review AI-generated code before deployment
Advise Government leaders on AI use-case feasibility, roadmaps, emerging technologies, and value measurement
Brief technical decisions to technical and non-technical audiences

Requirements

What you’ll need

Bachelor's degree in Engineering, Computer Science, Systems, or a related discipline
7+ years of relevant experience, including 7+ years of hands-on AI/ML engineering, enterprise architecture, cloud engineering, data engineering, or software engineering with direct technical delivery of AI-enabled systems
2+ years of hands-on experience with Generative AI, LLM integration, RAG, model evaluation, agentic AI, or production AI systems
Demonstrated experience architecting and delivering secure enterprise or federal AI solutions
Experience with AI system architecture, cloud AI platforms, APIs, data pipelines, MCP, vector databases, AI orchestration, model evaluation, and MLOps practices
Experience designing AI solutions in FedRAMP-authorized environments under a Zero Trust security architecture
AI-specific security and adversarial testing experience, including prompt injection, jailbreak, data-poisoning testing, and red teaming
Knowledge of Responsible AI, AI governance, privacy, and federal compliance requirements
Experience delivering technology conforming to Section 508 / WCAG 2.1 A and AA
Experience leading technical teams and advising Government or enterprise stakeholders
At least one current Generative AI or Machine Learning certification, including Microsoft Azure AI, AWS Generative AI/ML, Google Cloud, Databricks Generative AI Engineer, Snowflake SnowPro, NVIDIA Generative AI, Certified Artificial Intelligence Practitioner (CAIP), or equivalent
Must be a U.S. citizen or lawful permanent resident (green card holder)
Must reside in the Washington, DC metropolitan area
Must be able to work on-site at Government offices
Must be able to obtain and maintain a Government background investigation
Preferred: Multiple cloud architecture certifications and Kubernetes (CKA)
Preferred: Experience across Amazon Bedrock and SageMaker, Azure AI Foundry, Google Vertex AI, AWS Cloud AI development services, and open-weight model serving (vLLM, TGI)
Preferred: Familiarity with NIST AI RMF, OMB M-25-21 and M-25-22, OWASP Top 10 for LLM Applications, MITRE ATLAS, CMMI or ISO-based quality processes, and Agile program delivery
Preferred: An active federal background investigation

Benefits

Comp & 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