Description

• Design, build, deploy, secure, and operate production-ready AI agents using the AWS Strands Agents SDK and Amazon Bedrock AgentCore.

• Architect reusable agent platform components, APIs, deployment patterns, and controls for scalability, availability, observability, governance, and cost efficiency.

• Build AWS Lambda and Glue-based ingestion pipelines for parsing, metadata enrichment, chunking, embeddings, vector indexing, synchronization, and data-quality validation.

• Design Bedrock Knowledge Base and custom RAG solutions, selecting and tuning chunking, embedding, vector store, metadata, retrieval, reranking, and HNSW/IVF index strategies.

• Integrate automated retrieval, response-quality, regression, and safety evaluation into CI/CD release gates.

• Maintain a governed, versioned prompt library and develop platform services, automation, and integrations in Python and JavaScript.

• Implement monitoring, tracing, logging, alerting, security, and troubleshooting across agents and data pipelines.

• Collaborate with product, data, security, DevOps, and application teams to deliver reliable, maintainable AI solutions."

"• 6+ years of software, cloud, data, or platform engineering experience, including 3+ years designing AI/ML or Generative AI solutions on AWS.

• Hands-on experience building agents with the AWS Strands Agents SDK and deploying them through Amazon Bedrock AgentCore.

• Architecture-level knowledge of RAG, Bedrock Knowledge Bases, chunking, embedding models, vector stores, semantic retrieval, metadata filtering, and evaluation.

• Experience building scalable ingestion, embedding, indexing, reprocessing, and data-quality pipelines using AWS Lambda and Glue.

• Practical experience configuring and tuning HNSW, IVF, or comparable approximate nearest-neighbor indexes.

• Experience integrating AI and retrieval evaluation, regression checks, safety tests, and quality gates into CI/CD.

• Proficiency in prompt engineering, testing, versioning, and shared prompt-library design.

• Strong Python and JavaScript skills, including API integration, automated testing, packaging, debugging, and maintainable design.

• Knowledge of AWS IAM, networking, encryption, secrets, monitoring, least-privilege security, architecture documentation, and production runbooks.

Preferred Qualifications

• Experience with OpenSearch, pgvector, Pinecone, Redis, or comparable vector technologies, plus hybrid search, reranking, and advanced RAG patterns.

• Experience with infrastructure as code, containers, cloud-native CI/CD, and reusable APIs, SDKs, or engineering templates.

• Knowledge of LLM observability, hallucination analysis, prompt-injection defenses, guardrails, and responsible AI controls.

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.

Key Skills

Education

Bachelor's degree