Senior MLOps Engineer

Description

We are looking for a Senior MLOps Engineer to own 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 enables engineering teams to define, orchestrate, deploy, and observe AI agents at scale. The platform standardizes agent development across the organization using LangGraph and Strands Agents on AWS AgentCore Runtime, spanning agent framework design, runtime architecture, marketplace integration, CI/CD automation, and enterprise-grade observability, reducing 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 an immutable unit Manage AWS AgentCore Runtime versioning, including automatic version creation on image push and endpoint management for DEFAULT and named endpoints Design and enforce the agent promotion workflow from dev to qa to prod, embedding evaluation gates that guarantee quality before production release Establish agent rollback patterns that restore previous agent versions while validating that the prior version remains functional Configure AWS ECR for agent images, covering ARM64 tagging, lifecycle policies, and image signing to preserve agent immutability Integrate with the Agent Registry to auto-register agent versions along with metadata such as evaluation results and promotion status Collaborate 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 experience with deployment, promotion, or rollback workflows specifically for AI agents, such as agent evaluation gates, agent version comparison, or agent endpoint management Experience in versioning and lifecycle management for LLM agents or ML models Experience in immutable artifact versioning at enterprise scale using ECR and model registries Experience in CI/CD pipeline design with quality gates for AI systems English proficiency at B2 level or higher Nice to have Hands-on experience with AWS AgentCore Runtime versioning Familiarity with agent evaluation frameworks such as Langfuse, LangSmith, PromptLayer Experience with multi-environment agent promotion patterns Skills in agent version comparison and regression detection

Requirements

• 5+ years of experience in MLOps or DevOps engineering with AI/ML systems

• Hands-on experience with deployment, promotion, or rollback workflows specifically for AI agents, such as agent evaluation gates, agent version comparison, or agent endpoint management

• Experience in versioning and lifecycle management for LLM agents or ML models

• Experience in immutable artifact versioning at enterprise scale using ECR and model registries

• Experience in CI/CD pipeline design with quality gates for AI systems

• English proficiency at B2 level or higher

Responsibilities

• Define and maintain the agentic versioning model, treating agent container image, prompt configuration, tool bindings, and policy associations as an immutable unit

• Manage AWS AgentCore Runtime versioning, including automatic version creation on image push and endpoint management for DEFAULT and named endpoints

• Design and enforce the agent promotion workflow from dev to qa to prod, embedding evaluation gates that guarantee quality before production release

• Establish agent rollback patterns that restore previous agent versions while validating that the prior version remains functional

• Configure AWS ECR for agent images, covering ARM64 tagging, lifecycle policies, and image signing to preserve agent immutability

• Integrate with the Agent Registry to auto-register agent versions along with metadata such as evaluation results and promotion status

• Collaborate with engineering teams to standardize versioning and lifecycle practices across the agent estate

Seniority

• Senior

Nice to have

• Hands-on experience with AWS AgentCore Runtime versioning

• Familiarity with agent evaluation frameworks such as Langfuse, LangSmith, PromptLayer

• Experience with multi-environment agent promotion patterns

• Skills in agent version comparison and regression detection