Track Manager (Support & Operations)

Job Summary

Experience: 10-13 years of overall experience, including at least 2 years of production Generative AI implementation using Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Guardrails, and Bedrock AgentCore Runtime, Gateway, Memory, Identity, Evaluations, and Observability.

Job Summary: We are looking for an experienced Technical Lead - AWS Generative AI and Agentic AI to design, build, and deliver secure, scalable, production-grade AI solutions using Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Guardrails, and Bedrock AgentCore Runtime, Gateway, Memory, Identity, Evaluations, and Observability. The candidate will translate business requirements into measurable technical outcomes and apply strong engineering, observability, security, governance, and Responsible AI practices.

Key Responsibilities

Key Responsibilities:

• Lead the design and delivery of Generative AI and agentic AI solutions using Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Guardrails, and Bedrock AgentCore Runtime, Gateway, Memory, Identity, Evaluations, and Observability.
• Own end-to-end implementation from requirements and data preparation through evaluation, deployment, and production support.
• Translate business requirements into solution designs, technical plans, delivery estimates, and measurable acceptance criteria.
• Build secure integrations with enterprise applications, APIs, data platforms, and operational workflows.
• Establish evaluation, monitoring, tracing, cost, latency, safety, and reliability controls for production solutions.
• Drive reusable components, development standards, documentation, testing, CI/CD, and release governance.
• Lead engineering reviews, mentor team members, manage technical risks, and coordinate cross-functional delivery.
• Stay current with platform capabilities and recommend improvements based on validated business and technical value.

Skill Requirements

Must Have Skills:

• Strong experience with Amazon Bedrock and Models: Amazon Bedrock, Converse API, Amazon Nova, Anthropic Claude, cross-Region inference profiles.
• Strong experience with Bedrock AgentCore: Amazon Bedrock AgentCore Runtime, Harness, Memory, Gateway, Identity.
• Strong experience with RAG and Knowledge Bases: Amazon Bedrock Knowledge Bases, Amazon S3, Amazon OpenSearch Serverless, Amazon Aurora, Amazon Neptune Analytics.
• Strong experience with Agents and Orchestration: Agents for Amazon Bedrock, AWS Lambda, LangGraph, LangChain, Strands Agents.
• Strong experience with Prompt Engineering and Evaluation: Amazon Bedrock prompt management, Bedrock evaluations, Bedrock Guardrails.
• Strong experience with Security and Responsible AI: AWS IAM, AWS KMS, AWS Secrets Manager, Amazon Cognito, Amazon VPC.

   

  Preferred Skills:

  • Working knowledge of Deployment, LLMOps and Observability, including Amazon CloudWatch, AWS X-Ray, AWS CloudTrail, Amazon ECR.
  • Working knowledge of Data and Multimodal AI, including Amazon S3, AWS Glue, AWS Lake Formation, Amazon Athena.

Other Requirements

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
• 10-13 years of overall experience, including at least 2 years of production Generative AI implementation.
• Strong understanding of LLMs, RAG, agentic automation, prompt engineering, evaluation, and production AI operations.
• Ability to design secure and reliable APIs, tool integrations, data flows, identity controls, and failure-handling mechanisms.
• Experience implementing automated testing, version control, deployment pipelines, monitoring, and rollback practices.
• Good understanding of Responsible AI, privacy, safety, compliance, and enterprise security standards.
• Strong problem-solving skills and the ability to work effectively in a fast-paced, cross-functional environment.
• Strong written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.
• Proven experience leading complex AI/ML initiatives and resolving cross-team technical dependencies.
• Demonstrated ability to mentor engineers, review designs, and improve engineering quality and delivery predictability.