Senior AI​/ML Engineer

Senior AI/ML Engineer – Research, Development, and Implementation

InquisIT is seeking a Senior AI/ML Engineer to support the research, development, integration, and operational implementation of advanced artificial intelligence and machine learning solutions for federal customers and internal innovation initiatives. This role will primarily support Air Force Weather (AFW) modernization efforts while also helping identify and implement reusable AI-enabled capabilities across other InquisIT programs.

The ideal candidate is a senior technical engineer who bridges AI/ML engineering, cloud architecture, digital engineering, enterprise automation, and mission operations. They possess the ability to evaluate, implement, and operationalize AI, automation, and agentic AI technologies while balancing governance, security, identity management, auditability, observability, human oversight, cost, and operational readiness. This individual can move AI capabilities from research and prototype stages into secure, scalable, production environments that advance Air Force Weather modernization and broader organizational AI initiatives.

This is a REMOTE position with an active TOP SECRET security clearance required.

The Senior AI/ML Engineer will provide technical leadership and engineering support for AFW VPC 2.0 initiatives, helping apply modern digital engineering methods, cloud-native architectures, and ML Ops practices to advance Air Force Weather Cloud (AFWxC) and Weather Machine Learning Platform (WxMLP) capabilities.

• Apply digital engineering methods to support AFW cloud software integration, system planning, and architecture validation.
• Evaluate and integrate AI/ML capabilities into operational Air Force Weather environments.
• Assess current and future AFWxC architectures using modern cloud engineering and systems engineering practices.
• Support modernization of AFWxC and WxMLP architectures, including cloud-native storage, data management, and ML Ops workflows.
• Collaborate with engineering and data teams to optimize management of ML Ops datasets and weather-related data products.
• Support integration of WxMOE into AFWxC through scalable cloud-native data processing pipelines.
• Extend ML Ops capabilities into classified environments, including JWCC and air-gapped IL6 Kubernetes deployments.
• Participate in requirements analysis, architecture reviews, technology evaluations, and operational deployment planning.

• Identify, prototype, and implement AI-enabled solutions that improve productivity, workflow automation, knowledge management, documentation generation, and operational efficiency.
• Design and evaluate agentic AI solutions capable of orchestrating multi-step workflows while maintaining governance, security, auditability, and human oversight.
• Assess business and technical processes to identify practical AI use cases that improve delivery speed and workforce effectiveness.
• Develop reusable AI patterns and automation capabilities that can be leveraged across multiple programs and internal operations.

• Anthropic Claude / Claude Enterprise
• Service Now AI Agents and Now Assist
• AWS Bedrock Agents
• IBM watsonx Orchestrate
• UiPath AI Agents and Autopilot

• Lang Chain
• Lang Graph
• CrewAI
• Auto Gen
• Semantic Kernel
• n8n
• Similar enterprise orchestration and workflow frameworks

• Active Top Secret security clearance required; TS/SCI eligibility preferred.
• Advanced experience designing, developing, and deploying AI/ML solutions in cloud or hybrid-cloud environments.
• Strong understanding of ML Ops practices, including model development, training, deployment, monitoring, automation, and sustainment.
• Experience with cloud-native storage, distributed data processing, and scalable data pipeline architectures.
• Hands‑on experience with Kubernetes, containerized workloads, Dev Sec Ops  practices, CI/CD pipelines, and cloud engineering.
• Experience evaluating system architectures, validating technical designs, and…