Senior MLOps Engineer - Agentic Versioning

We are seeking a Senior MLOps Engineer to take ownership of the agentic versioning model, promotion workflow, and rollback patterns across the agent estate, contributing to an Enterprise Agent Development Platform — a production-grade, cloud-native ecosystem that empowers engineering teams to define, orchestrate, deploy, and observe AI agents  platform unifies agent development across the organization through Lang Graph and Strands Agents on AWS Agent Core Runtime, covering agent framework design, runtime architecture, marketplace integration, CI/CD automation, and enterprise-grade observability, cutting agent development from months to days while enforcing consistent security, quality, and governance standards.

• Define and maintain the agentic versioning model, treating agent container image, prompt configuration, tool bindings, and policy associations as one immutable unit
• Oversee AWS Agent Core Runtime versioning, including automatic version creation upon image push and endpoint management for DEFAULT and named endpoints
• Architect and enforce the agent promotion workflow from dev to qa to prod, embedding evaluation gates that ensure quality prior to production release
• Build agent rollback patterns that restore previous agent versions while confirming that the prior version remains functional
• Configure AWS ECR for agent images, including ARM
  64 tagging, lifecycle policies, and image signing to maintain agent immutability
• Integrate with the Agent Registry to auto-register agent versions together with metadata such as evaluation results and promotion status
• Partner with engineering teams to standardize versioning and lifecycle practices across the agent estate

• 5+ years of experience in MLOps or Dev Ops engineering with AI/ML systems
• Hands‑on expertise in deployment, promotion, or rollback workflows specifically for AI agents, such as agent evaluation gates, agent version comparison, or agent endpoint management
• Background in versioning and lifecycle management for LLM agents or ML models
• Proficiency in immutable artifact versioning at enterprise scale using ECR and model registries
• Skills in CI/CD pipeline design with quality gates for AI systems
• Proficiency in English at B2 level or higher
• Nice to have Hands‑on competency in AWS Agent Core Runtime versioning Understanding of agent evaluation frameworks such as Langfuse, Lang Smith, Prompt Layer Familiarity with multi‑environment agent promotion patterns Expertise in agent version comparison and regression detection