AI Engineer - GCP

UST; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

UST is seeking an experienced AI/ML Engineer with strong software engineering and AWS expertise to design, build, and operate production‑grade AI services. The role involves integrating APIs, deploying on AWS, and implementing RAG, tool use, and prompt orchestration.

You will work with cross‑functional teams to deliver scalable, containerized solutions and contribute to CI/CD pipelines and IaC frameworks. The ideal candidate has hands‑on experience with Bedrock, MCP, and knowledge graphs.

Qualifications

• 6+ years of professional experience in software, data, or AI/ML engineering.
• 3+ years of hands‑on experience building and operating production services on AWS.
• Strong proficiency in Python with solid software engineering fundamentals, including testing, code reviews, and version control.
• Experience with AWS services such as Bedrock, Lambda, ECR, S3, API Gateway, IAM, CloudWatch.
• Experience designing and integrating APIs and backend services.
• Working knowledge of LLM application patterns including Retrieval‑Augmented Generation (RAG) and prompt orchestration.
• CI/CD and containerization experience with Docker.
• Infrastructure‑as‑Code experience with AWS CDK, Terraform, or CloudFormation.
• Strong communication and collaboration skills.

Responsibilities

• Design, develop, and operate scalable production services on AWS.
• Build AI/ML and LLM‑powered applications using modern patterns.
• Develop and integrate APIs and services exposing data, tools, and AI capabilities to client apps.
• Implement retrieval‑augmented generation (RAG), prompt orchestration, tool use, and search/retrieval solutions.
• Develop and maintain CI/CD pipelines and automated deployment processes.
• Build containerized applications using Docker and implement infrastructure using IaC.
• Integrate AI agents and tool ecosystems using MCP or comparable frameworks.
• Work with knowledge graphs, context graphs, and graph databases where applicable.
• Develop evaluation and retrieval pipelines to measure AI application quality.
• Collaborate with engineering, data, AI/ML, DevOps, and cross‑functional teams.
• Deliver solutions independently within an existing architecture with minimal supervision.

Skills

Python

AWS

LLMs

APIs

CI/CD

Docker

GitHub Actions

Terraform

CDK

Tools

AWS Bedrock

Lambda

ECR

S3

API Gateway

IAM

CloudWatch

MCP

Job description

Role Description

We are looking for an experienced AI/ML Engineer with strong software engineering and AWS expertise to build, integrate, and operate production-grade AI and data services. The ideal candidate will have hands‑on experience with Python, AWS, Generative AI/LLM applications, APIs, CI/CD, containerization, and infrastructure‑as‑code.

• Design, develop, and operate scalable production services on AWS.
• Build AI/ML and LLM‑powered applications using modern application patterns.
• Develop and integrate APIs and services that expose data, tools, and AI capabilities to client applications.
• Implement retrieval‑augmented generation (RAG), prompt orchestration, tool use, and search/retrieval solutions.
• Develop and maintain CI/CD pipelines and automated deployment processes.
• Build containerized applications using Docker and implement infrastructure using IaC.
• Integrate AI agents and tool ecosystems using MCP or comparable frameworks.
• Work with knowledge graphs, context graphs, and graph databases where applicable.
• Develop evaluation and retrieval pipelines to measure and improve AI application quality.
• Collaborate with engineering, data, AI/ML, DevOps, and other cross‑functional teams.
• Work independently within an existing architecture and codebase and deliver solutions with minimal supervision.

Key Responsibilities

• Design, develop, and operate scalable production services on AWS.
• Build AI/ML and LLM‑powered applications using modern application patterns.
• Develop and integrate APIs and services that expose data, tools, and AI capabilities to client applications.
• Implement retrieval‑augmented generation (RAG), prompt orchestration, tool use, and search/retrieval solutions.
• Develop and maintain CI/CD pipelines and automated deployment processes.
• Build containerized applications using Docker and implement infrastructure using IaC.
• Integrate AI agents and tool ecosystems using MCP or comparable frameworks.
• Work with knowledge graphs, context graphs, and graph databases where applicable.
• Develop evaluation and retrieval pipelines to measure and improve AI application quality.
• Collaborate with engineering, data, AI/ML, DevOps, and other cross‑functional teams.
• Work independently within an existing architecture and codebase and deliver solutions with minimal supervision.

Mandatory Skills & Experience

• 6+ years of professional experience in software, data, or AI/ML engineering.
• 3+ years of hands‑on experience building and operating production services on AWS.
• Strong proficiency in Python with solid software engineering fundamentals, including testing, code reviews, and version control.
• Hands‑on experience with AWS services such as:
• Amazon Bedrock
• AWS Lambda
• Amazon ECR
• Amazon S3
• API Gateway
• IAM
• CloudWatch
• Experience designing and integrating APIs and backend services.
• Working knowledge of LLM application patterns, including:
• Retrieval‑Augmented Generation (RAG)
• Prompt orchestration
• Tool/function calling
• AI agent integration
• Strong understanding of CI/CD and containerization, particularly Docker.
• Hands‑on experience with CI/CD tools such as GitHub Actions, Jenkins, or similar.
• Experience with Infrastructure‑as‑Code using AWS CDK, Terraform, or CloudFormation.
• Strong communication and collaboration skills.
• Ability to quickly understand an existing architecture/codebase and contribute independently.

Preferred / Good‑to‑Have Skills

• Hands‑on experience with Model Context Protocol (MCP) or similar agent/tool integration frameworks.
• Experience with Amazon Bedrock AgentCore Gateway or Runtime.
• Experience with knowledge graphs, context graphs, or graph databases.
• Experience building or optimizing search and retrieval systems and evaluation pipelines.
• Strong hands‑on experience with AWS CDK and GitHub Actions.
• Familiarity with AI governance, model evaluation, and compliance frameworks.
• Experience with software supply‑chain security.
• Experience with multi‑tenant cost attribution and cost optimization at scale.
• Contributions to open‑source AI platforms, MCP projects, or DevOps tooling.

Key Technologies

Python | AWS | Amazon Bedrock | Bedrock AgentCore | Lambda | ECR | S3 | API Gateway | IAM | CloudWatch | MCP | RAG | LLMs | AI Agents | Docker | GitHub Actions | Jenkins | AWS CDK | Terraform | CloudFormation | Knowledge Graphs | Search & Retrieval

Ideal Candidate Profile

The ideal candidate is a hands‑on engineer rather than an architect, with strong coding and implementation experience across Python, AWS, Generative AI/LLMs, APIs, DevOps, and cloud‑native services. Experience with MCP, Bedrock AgentCore, RAG, knowledge graphs, and AI evaluation will be a strong advantage.

Skills

AWS, Devops, Google Cloud Platform