Senior Applied AI Architect
Req number:
R8010
Employment type:
Full time
Worksite flexibility:
Remote
Job Summary
CAI is hiring a Sr. Applied AI Architect to serve as the primary technical engine behind our applied AI delivery across all four strategic motions. This is a builder’s role at the intersection of deep technical execution and strategic advisory
Job Description
We are seeking a highly skilled and experienced Sr. Applied AI Architect to join our IT team. This position will be full-time, remote, and is a salaried position.
What You'll Do
- Lead technical design for agentic AI systems, LLM integrations, MCP-based orchestration, and multi-model workflows in internal and external delivery environments
- Own build-vs-buy decisions for AI tooling across use cases, working with the CTO organization and design partners
- Develop reusable architectural patterns, integration blueprints, and technical playbooks that scale across CAI’s delivery organization
- Drive technical POC development from internal initiatives through to client-ready case studies, architecture and implementation
- Serve as the technical lead and credibility anchor for AI solution conversations with executives, clients, and procurement stakeholders
- Work alongside functional and motion owners to determine whether and how AI applies, then own the technical approach and execution
- Pressure-test AI feasibility on CTO assessments, POC scoping, and motion-level AI roadmaps
- Mentor and develop junior AI technical staff; contribute to the Applied AI Delivery Team model
- Maintain deep, working knowledge of the enterprise AI landscape: LLMs (Anthropic Claude, OpenAI, Gemini), agentic frameworks, MCP architecture, Databricks, vector databases, and emerging tools
- Apply hands-on fluency across the full stack CAI deploys; AI/ML frameworks, integration patterns, API design, cloud platforms (AWS, Azure), and security controls relevant to commercial and public sector public sector
- Ensure architectural choices align with CAI’s governance standards, NIST AI framework, GovRAMP requirements, and client-specific compliance environments
- Bring an evidence-based perspective on AI capability and limitations to keep initiatives grounded, realistic, and defensible.
- Package internal AI delivery results into reusable inputs for client-ready case studies, RFP content, and competitive positioning. Build the technical artifacts that move work forward: solution designs, architecture diagrams, integration specs, feasibility assessments, and deployment guides
What You'll Need
Required
- 8-10+ years of experience in applied AI, enterprise software architecture, or AI/ML engineering with at least 3 years in a senior or lead role
- Demonstrated track record of designing and delivering production-grade AI solutions end-to-end; hands-on, not advisory
- Deep fluency with large language models, agentic AI frameworks, prompt engineering, and MCP or similar orchestration architectures
- Hands-on experience with enterprise AI platforms: Anthropic Claude, OpenAI, Databricks, Azure AI / OpenAI Service, AWS Bedrock, or equivalent
- Strong system design and integration architecture skills: APIs, data pipelines, event-driven systems, and cloud infrastructure
- Ability to operate credibly across technical depth (code environments, architecture review) and executive conversation
- Experience working in regulated or government-adjacent environments, with familiarity with FedRAMP, GovRAMP, NIST, or SOC 2 compliance requirements
- Strong communication skills: able to translate complex technical architecture into executive-ready artifacts and client-facing narratives
- Bachelor's degree in computer science, Engineering, or a related technical field required; master's or advanced degree preferred; or a related field required; or the equivalent combination of education, technical certifications or training, or work experience
Desired
- Experience delivering AI solutions in state and local government, public sector managed services, or workforce services environments
- Hands-on experience with Anthropic’s Model Context Protocol (MCP) and multi-agent orchestration frameworks (LangChain, AutoGen, CrewAI, or equivalent)
- Track record of building reusable AI architectural assets, patterns, blueprints, frameworks, that scale beyond a single engagement
- Experience contributing to AI governance frameworks, responsible AI posture, or client-facing compliance advisory
- Certifications in relevant platforms (AWS, Azure, Databricks, Google Cloud AI) or AI governance frameworks (ISACA, NIST AI RMF)
- Prior experience in a professional services or consulting delivery model with multiple concurrent client engagements.
Physical Demands
- Ability to safely and successfully perform the essential job functions consistent with the ADA and other federal, state, and local standards
- Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc
- Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor