AI Architect - 1683

SARA•Colorado Springs, CO

5d•Onsite

About The Position

Scientific Applications & Research Associates, Inc. (SARA) is seeking a talented, motivated, and imaginative AI Architect to join its High Power Electromagnetics Division (HPEM) in Colorado Springs, CO. This role will work alongside the current AI Architect to expand and accelerate the adoption of secure, practical AI solutions across business and technical functions. The position involves hands-on architecture and implementation, technical leadership, and a focus on secure onsite/private LLM deployments, enterprise data integration, and production-ready AI workflows. The AI Architect will contribute to shared platform architecture, governance, evaluation standards, and production lifecycle management, taking ownership of initiatives from requirements definition through deployment and improvement. Collaboration with executive leadership, IT, cybersecurity, data owners, engineering teams, and external partners is key to delivering AI-enabled workflows that enhance decision-making, automate analysis, and increase efficiency. Success will be measured by adoption, business value, and reliable production operations.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
8 – 10 years of professional experience in AI, software engineering, data science, enterprise systems, or a related technical field
5+ years of experience leading complex technical initiatives, including architecture and delivery responsibilities
Demonstrated hands-on experience deploying, integrating, and maintaining AI systems
Proven ability to deliver and support systems beyond proof-of-concept
Strong understanding of LLMs and generative AI concepts, capabilities, limitations, and architectural tradeoffs
Experience with LLM deployment using open-source and/or proprietary models
Experience with RAG architectures, embedding models, and vector databases
Experience with AI infrastructure in on-premises, private cloud, or hybrid environments
Experience with enterprise data systems, including SQL databases, document repositories, and APIs
Experience with authentication, authorization, and secure application integration
Experience with evaluation and monitoring of LLM applications and supporting infrastructure
Proficiency in Python or another programming language used to build AI applications and integrations
Familiarity with AI tooling ecosystems such as Open WebUI, LangChain, or LlamaIndex
Familiarity with MCP and client-server architecture
Familiarity with model lifecycle management and the maintenance of RAG data sources and retrieval pipelines
Familiarity with authentication and security technologies such as JWT, OAuth, LDAP, and API key management
Understanding of GPU infrastructure, inference performance, capacity planning, and cost tradeoffs
Strong data governance and security awareness
Ability to collaborate with another senior architect, align on shared standards, and independently execute assigned initiatives
Strong communication skills across technical and non-technical audiences
U.S. citizen with the ability to obtain and maintain a DoD security clearance
May require moderate physical effort, including standing, sitting, use of hands while performing duties, and carrying or lifting up to 50 pounds
Working environment is indoor, moderately quiet, reasonably clean, well-lighted and well-ventilated; moderate physical hazards may exist

Nice To Haves

Master’s degree or higher in a related field
10 – 12 years of relevant professional experience, including substantial experience deploying and maintaining AI systems
Experience deploying onsite or air-gapped AI systems
Background in Government Contracting and/or environments involving sensitive or proprietary information
Experience delivering AI solutions across multiple business or engineering functions
Experience with cloud platforms such as AWS, Azure, or GCP
Experience with high-level IT network and systems architecture
Experience with automated testing, CI/CD, and repeatable deployment practices for AI application
AI product management or AI platform ownership experience

Responsibilities

Partner with the current AI Architect to advance the enterprise AI strategy, roadmap, and architectural standards
Lead assigned AI initiatives from discovery and requirements definition through implementation, deployment, and ongoing support
Work with business and technical stakeholders to identify, prioritize, and deliver high-value AI use cases
Architect, implement, and maintain secure onsite and private LLM deployments
Evaluate and select AI tools, models, platforms, and architectures based on capability, security, maintainability, and cost
Design and implement Retrieval-Augmented Generation (RAG) pipelines, enterprise data integrations, model hosting, and inference workflows
Develop secure integrations with enterprise applications, databases, and services, including Model Context Protocol (MCP) interfaces where appropriate
Contribute to reusable platform capabilities, integration patterns, and deployment practices that enable adoption across additional business areas
Partner with IT and cybersecurity to ensure AI systems meet applicable security, privacy, access control, and governance requirements
Establish and apply evaluation methods for model quality, retrieval accuracy, reliability, performance, and business outcomes
Develop and maintain AI usage guidelines, guardrails, and technical documentation in collaboration with the current AI Architect
Support internal training, user onboarding, and adoption efforts
Monitor deployed AI systems and improve performance, usability, resource utilization, and business value over time