Role Description

Job Summary

We are seeking a highly skilled Senior AI Platform Engineer with strong expertise in AWS Bedrock, LLMs, RAG, and Vectorization/Embeddings to design, build, and operate scalable AI-powered services in AWS. The ideal candidate will have experience developing production-grade AI applications, integrating enterprise data sources, building retrieval systems, and delivering secure, observable, and maintainable cloud-native solutions. This role requires strong software engineering fundamentals, deep AWS experience, and the ability to collaborate effectively across multidisciplinary teams while delivering independently within an established architecture.

Key Responsibilities

- Design, develop, and operate production-grade AI services and applications using AWS Bedrock, LLMs, and RAG architectures.
- Build intelligent retrieval solutions leveraging Vectorization / Embeddings, semantic search techniques, and contextual information retrieval.
- Design and integrate APIs and microservices that expose AI-powered capabilities to client applications.
- Develop and maintain scalable serverless solutions using AWS Lambda and related AWS services.
- Implement retrieval pipelines involving Chunking, embedding generation, indexing, and context enrichment.
- Build and optimize search and retrieval systems to improve relevance, accuracy, and user experience.
- Work with Knowledge graphs / Context graphs / Graph databases to enhance contextual reasoning and information discovery.
- Collaborate with engineering, product, and architecture teams to deliver AI platform capabilities aligned with business objectives.
- Implement CI/CD best practices,



containerization, and automated deployment pipelines.
- Ensure solution reliability through testing, monitoring, logging, and operational excellence practices.
- Contribute to the continuous improvement of cloud infrastructure, development processes, and platform capabilities.
- Participate in code reviews, design discussions, and technical decision-making activities.

Required Skills

Proficient

- RAG
- LLMs
- AWS Bedrock
- Vectorization / Embeddings

Intermediate

- OpenSearch
- Chunking
- Knowledge graphs / Context graphs / Graph databases
- AWS Lambda

Experience

- 6+ years of professional experience in software engineering, data engineering, or AI/ML engineering.
- 3+ years of experience building and operating production services on AWS.
- Solid proficiency in Python and solid software engineering fundamentals including testing, code review, and version control.
- Experience building and integrating APIs and enterprise-grade services.
- Working knowledge of modern LLM application patterns and AI platform development.
- Experience with Docker-based containerization and CI/CD implementations.
- Experience with infrastructure-as-code practices using AWS cloud ecosystems.

Preferred Qualifications

- Experience with Model Context Protocol (MCP) or similar agent integration frameworks.
- Experience with Amazon Bedrock AgentCore Gateway or Runtime.
- Familiarity with AI governance, evaluation, and compliance frameworks.
- Understanding of supply chain security and multi-tenant cost attribution.
- Contributions to open-source AI platform, MCP, or DevOps tooling.

Skills AWS, AWS CloudFormation, AWS Lambda

📌 Senior AI Platform Engineer (AWS Bedrock & RAG) (Ahmedabad)
🏢 UST
📍 Ahmedabad