AI Engineer

CAСI is hiring an AI Engineer to support its AI Center of Excellence, delivering production-ready GenAI applications through short, rotational engagements. The work includes building RAG pipelines, conversational AI platforms, and multi-agent systems, with an emphasis on operationalization, knowledge transfer, and improvement of a reusable solution catalog.

Responsibilities

• Deliver production-ready AI solutions in 1–2 month rotations, including RAG pipelines, conversational platforms, and multi-agent systems, tailored to each program’s mission and technology stack.
• Build and customize AI solutions using vector databases, orchestration frameworks, and managed AI services, while implementing observability, security, and cost controls.
• Integrate LLM APIs and AI services into existing workflows, apply responsible AI guardrails, configure monitoring/alerting, and troubleshoot integration issues across cloud and on-prem environments.
• Lead hands-on training, create documentation, and pair-program with teams to support independent operation and ongoing evolution of AI applications.
• Improve existing templates, create reusable patterns, and document new techniques based on field experience.
• Confirm operational independence through structured handoff and validation processes.
• Explore emerging GenAI tools, evaluate federal use-case applicability, and share insights through demos and documentation.

Required Qualifications

• 3–5 years building production applications with Python/JavaScript, Git workflows, and modern development practices.
• Practical experience with LLM-powered apps, agent patterns, RAG, prompt engineering, vector databases, and observability concepts; hands-on experimentation preferred.
• Ability to monitor AI performance (latency, cost, quality), address common failure modes, and apply responsible AI practices such as bias detection and guardrails.
• Strong background designing, implementing, and troubleshooting RESTful and event-driven integrations.
• Experience with AWS/Azure/GCP, containerization, CI/CD, IaC concepts, and secure API/key management.
• Understanding of basic ML concepts and how they apply to LLM systems.
• Proven ability to deliver solutions quickly in unfamiliar environments with evolving requirements.
• Strong communication skills, including creating clear documentation and teaching complex AI concepts.
• Ability to make trade-offs under pressure, prioritize working solutions, and leverage reusable templates.
• Active user of modern AI tools, staying current through experimentation and community engagement.
• Experience with GitLab, Jira, and iterative delivery.
• Ability to obtain and maintain a Top Secret clearance.

Preferred Qualifications

• Experience deploying agentic AI systems, using observability tools, vector databases, guardrails, embeddings, and structured outputs.
• AWS (Bedrock/GovCloud), Azure OpenAI, Kubernetes, Terraform, and CI/CD pipeline experience.
• Proficiency in JS/TS/Python for front-end/back-end development and modern frameworks such as React or FastAPI.
• Experience leading client engagements, context-switching across projects, and delivering strong knowledge transfer.
• Familiarity with DoD/federal missions, security requirements, and compliance frameworks (including ATO and NIST).
• History of open-source work, technical writing, conference speaking, or similar community involvement.
• Security+ , AWS certifications, or other relevant technical credentials.

Technologies

• Python, JavaScript, Git
• LLM-powered apps, LLM APIs, AI services, RAG, prompt engineering
• Vector databases, embeddings
• Observability concepts, monitoring/alerting
• RESTful integrations, event-driven integrations
• AWS, Azure, GCP, managed AI services
• Orchestration frameworks, multi-agent systems
• Containerization, CI/CD, IaC
• Secure API/key management
• GitLab, Jira

Compensation and Location

Location: Denver, CO (onsite). Salary range: USD 82,100 to 172,400 per year.

Benefits

• Healthcare
• Wellness
• Financial
• Retirement
• Family support
• Continuing education
• Time off benefits
• Competitive compensation
• Benefits and learning and development opportunities

What You Can Expect

• A culture of integrity
• An environment of trust
• A focus on continuous growth
• Flexible time off benefit
• Access to robust learning resources