AI Engineer​/Cloud Engineer

AI Engineer / Cloud Engineer

Core Stack: AWS Bedrock Agent Core
• Azure AI Foundry
• MCP Governance

Function: Foundations / Infrastructure & Operations

Level: Senior / Staff

Type: Full Time

Location: Remote / Hybrid

Reports to: Director, AI Architecture

The Foundations team serves as the enterprise AI governance control plane for Infrastructure & Operations (I&O), responsible for the infrastructure, observability, security, and policy layer across a multi‑cloud AI agent ecosystem.

We are seeking a senior AI/Cloud Engineer to design, build, and operate production‑grade AI agent infrastructure across Amazon Web Services Bedrock Agent Core and Microsoft AI Foundry, with deep integration across MCP (Model Context Protocol) connectors, LLM gateways, and enterprise data systems.

This role sits at the intersection of AI platform engineering, cloud infrastructure, governance, and enterprise security. You will partner closely with the I&O Architecture Engineering team to ensure AI agents are observable, measurable, secure, and fully governed across the enterprise estate.

• Design and deploy production AI agent workloads on AWS Bedrock Agent Core, including runtime configuration, memory stores, and Data Dog observability instrumentation.
• Build and maintain Azure AI Foundry agent pipelines with Application Insights telemetry, Azure APIM‑based token attribution, and Azure Monitor integration for safety and red‑teaming signals.
• Architect MCP connector infrastructure, including tool‑call routing, RBAC enforcement, OAuth2 / Entra , and end‑to‑end audit logging.
• Maintain and evolve the enterprise LLM gateway as the centralized routing, policy enforcement, and instrumentation layer across Bedrock, Azure OpenAI, and Claude‑based endpoints.

• Instrument agent systems to capture Tier 1 audit KPIs such as tool‑call completeness, policy violations, RBAC coverage, and authentication failure rates aligned with compliance requirements.
• Define per‑connector security policies ensuring Finance, HR, Legal, and Client data systems remain fully governed and least‑privileged.
• Build unified observability dashboards across Cloud Watch, Azure Monitor, and Data Dog for AI system health and executive reporting.
• Participate in CDR (Critical Design Review) processes for all AI agent deployments, ensuring adherence to reliability, security, and observability standards.
• Design SOC 2‑aligned audit log pipelines for all agent tool‑calls to support compliance and forensic traceability.

• Integrate AI agent systems with enterprise platforms such as Service Now, Data Dog, Apptio/Cloudability, and internal data platforms via MCP connectors and REST APIs.
• Support CI/CD automation for AI agents using Git Hub Actions, including environment promotion, rollback strategies, and pipeline replay mechanisms.

• Define and instrument agent KPIs including task completion rate, hallucinated tool‑call detection, escalation rate, and context efficiency metrics.
• Leverage AWS Agent Core evaluation frameworks and Azure AI Foundry evaluation tooling to assess groundedness, safety, tool accuracy, and reliability.
• Build golden dataset regression suites to detect performance degradation across model updates, prompt changes, and connector modifications.

• AWS Bedrock Agent Core (production workloads)
• Azure AI Foundry (agent pipelines & evaluation systems)
• AWS Lambda / EKS
• Azure API Management (APIM)
• Cloud Watch (metrics, logs, traces)
• Azure Monitor + Application Insights
• LLM Gateway architecture experience
• MCP (Model Context Protocol) servers
• OAuth2 / Entra  / IAM‑based credential scoping

• 5+ years software/platform engineering experience; 2+ years in AI/ML infrastructure or LLM‑based systems
• Strong proficiency in Python;
  Type Script/Node.js preferred for orchestration layers
• Experience with REST APIs, async processing, and event‑driven architectures
• Hands‑on CI/CD experience (Git Hub Actions preferred)
• Infrastructure‑as‑Code and container‑based…