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 empowering engineering teams to define, orchestrate, deploy, and observe AI agents at scale. The platform unifies agent development across the organization through LangGraph and Strands Agents on AWS AgentCore 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. Responsibilities Define and maintain the agentic versioning model, treating agent container image, prompt configuration, tool bindings, and policy associations as a single immutable unit Manage AWS AgentCore 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 prior agent versions while confirming that the previous version remains functional Configure AWS ECR for agent images, addressing ARM64 tagging, lifecycle policies, and image signing to safeguard agent immutability Integrate with the Agent Registry to automatically register agent versions along with metadata such as evaluation outcomes and promotion status Partner with engineering teams to standardize versioning and lifecycle practices across the agent estate Requirements 5+ years of experience in MLOps or DevOps engineering with AI/ML systems Hands-on expertise in deployment, promotion, or rollback workflows specifically built 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 leveraging ECR and model registries Skills in CI/CD pipeline design with quality gates applied to AI systems English proficiency at B2 level or higher Nice to have Hands-on competency in AWS AgentCore Runtime versioning Familiarity with agent evaluation frameworks, including Langfuse, LangSmith, PromptLayer Expertise in multi-environment agent promotion patterns Capability to perform agent version comparison and regression detection