Artificial Intelligence ("AI") Architect
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Role details
Tech stack
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Job description
The Senior AI Platform & Services Engineer is a senior hands-on technical position responsible for engineering, administering, integrating, operating, and continuously improving enterprise AI platforms and services. The position provides technical leadership across a multi-platform AI environment initially centered on OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini. The engineer establishes repeatable technical patterns, operational standards, integrations, access controls, monitoring, service-management processes, and governance implementation so AI capabilities can be operated securely and reliably as managed enterprise services. This role is expected to remain hands-on and is not primarily a consulting, policy-only, or custom model-research position., * Engineer, administer, and continuously improve enterprise AI platforms and the supporting technical services required to operate them at scale.
- Serve as a hands-on technical subject-matter resource across OpenAI/ChatGPT, Microsoft Copilot, Google Gemini, and related enterprise AI technologies.
- Design and implement technical patterns for APIs, connectors, agents, orchestration, knowledge sources, retrieval- augmented generation (RAG), automation, and integrations with enterprise systems.
- Establish platform administration, environment management, access control, configuration, service onboarding, change/release, and lifecycle-management standards.
- Design and implement identity patterns including SSO, RBAC, privileged access, service identities, scopes/permissions access reviews, secrets, and least-privilege controls as applicable.
- Translate approved governance, security, privacy, legal, compliance, records, and data-management requirements into enforceable technical configurations and operating controls.
- Evaluate data flows, model/provider interactions, knowledge sources, connectors, and integrations to identify technical risks, dependencies, logging requirements, and control points.
- Establish monitoring, logging, alerting, auditability, usage reporting, cost/consumption visibility, licensing oversight, and operational performance metrics for AI services.
- Own or lead troubleshooting of complex platform, integration, authentication, authorization, data-access, agent, performance, and service-availability issues.
- Evaluate new AI products, models, platform capabilities, agents, and features and define technical testing, pilot, release, and support-readiness requirements.
- Develop and maintain technical architecture documentation, standards, configuration baselines, runbooks, support models, knowledge articles, and operational procedures.
- Define escalation paths and support boundaries for AI-related incidents and service requests and coordinate with vendors and internal technical teams as needed.
- Identify and implement automation opportunities that reduce manual administration and improve consistency, reliability, observability, and governance.
- Provide technical mentoring and guidance to AI Platform Engineers and other support resources while maintaining hands-on ownership of critical engineering work.
- Partner with cybersecurity, cloud/infrastructure, identity, application, data, architecture, service-management, procurement, legal/compliance, and business teams on AI service delivery.
Requirements
- Approximately 4 - 7+ years of professional experience in cloud engineering, systems engineering, platform engineering, DevOps, enterprise application administration, automation, security engineering, or comparable technical disciplines.
- Approximately 2+ years of meaningful experience with AI, intelligent automation, machine learning platforms, generative AI, or closely related enterprise technologies is preferred; equivalent depth demonstrated through hands-on delivery may be considered.
- Demonstrated experience engineering or operating complex enterprise cloud/SaaS platforms, integrations, identity controls, APIs, and support processes.
- Strong troubleshooting capability and experience leading technical resolution of multi-system issues involving applications, cloud services, identity, permissions, APIs, or data access.
- Ability to translate architectural, security, privacy, governance, or compliance requirements into practical technical designs and operational controls.
- Strong systems-thinking skills and the ability to understand how AI platforms interact with identity, data, applications, networks, cloud services, security controls, and operational processes.
- Ability to design practical service structures around rapidly changing technology without overengineering or losing operational supportability.
- Ability to evaluate trade-offs across platform capability, security, privacy, cost, user experience, maintainability, and compliance requirements.
- Strong technical documentation, standards development, and communication skills for both engineering and governance audiences.
- Ability to mentor engineers, provide technical direction, coordinate across teams, and maintain ownership through implementation and steady-state operations., * Hands-on experience with at least two of the following ecosystems: OpenAI/ChatGPT and OpenAI APIs; Microsof Copilot/Copilot Studio/Azure AI services; Google Gemini/Vertex AI/Google Cloud.
- Experience implementing enterprise AI agents, RAG/grounding, knowledge integration, enterprise search, tool/function calling, model routing, or API orchestration patterns.
- Experience with PowerShell, Python, REST APIs, JSON, CI/CD or infrastructure automation, low-code workflow tools, or comparable automation technologies.
- Experience with enterprise IAM, Microsoft Entra ID or comparable identity platforms, OAuth/OIDC/SAML, RBAC, privileged access, service principals/service accounts, secrets, and access reviews.
- Experience implementing security, privacy, data-loss prevention, logging/audit, records/data-handling, responsible AI, or AI governance requirements in technology platforms.
- Experience establishing IT service-management models including incident, request, change, problem, knowledge, service ownership, escalation, monitoring, and operational reporting.
- Experience operating technology in a regulated, government, large-enterprise, or other control-intensive environment.
Education Required:
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related technical discipline, or an equivalent combination of education and progressively responsible professional experience.
Benefits & conditions
- A certified minority-owned small business government contractor with capabilities related to Public Health IT, Criminal Justice, Transportation, and Defense.
- A certified service-disabled veteran-owned company with a proud 46-year track record of providing successful innovative solutions for our government customers.
- A drug-free workplace in accordance with the Drug-Free Workplace Act of 1988.
- Applicants who have a signed offer of employment or contractor agreement are subject to:
- the pre-employment testing protocol: o background investigation o drug screening
Our Employees:
- Are actively working on next-generation technology projects with the U.S. Department of Veterans Affairs, CDC, and a wide array of Federal, State, and Local agencies throughout the United States
- Are eligible for wide-ranging benefits and perks, including but not limited to:
- Comprehensive Health Insurance with PPO and HDHP/HSA options
- Dental Insurance
- Vision Insurance
- Short/Long-Term Disability
- Group Life Insurance - Company Paid
- Voluntary Life Insurance
- 401(k) Plan with Employer Match
- Paid Time Off (Vacation/Sick)
- Holiday Pay - Company Paid Federal Holidays
- Professional Certification Incentive Plan
- Employee Referral Plan
- Technology Exposure
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