AI/ML Engineer – AWS & Python

UST; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

UST in Bengaluru, India is seeking an experienced Senior MCP & Python Platform Engineer to design, build, deploy, and operate production-grade AI services and platform components. The role emphasizes MCP Server Management, MCP Observability, Python development, and cloud-native AWS architectures.

You will implement APIs, support LLM workflows such as RAG, and build containerized workloads with Docker while creating CI/CD pipelines and governance for secure, scalable platforms.

Qualifications

• 6+ years of professional experience in software, data, or AI/ML engineering.
• 3+ years of direct experience building and operating production services on AWS.

Responsibilities

• Design, develop, deploy, and maintain scalable platform services using Python.
• Manage and operate MCP Server Management capabilities for AI-powered applications and tool integrations.
• Implement MCP Observability with monitoring, logging, and tracing for MCP-based services.
• Build and operate production services on AWS using cloud-native services and best practices.
• Design and integrate APIs exposing data, tools, and AI capabilities to client apps.
• Develop and support LLM-based workflows including retrieval-augmented generation and tool integration patterns.
• Build and maintain containerized workloads using Docker.
• Create and support CI/CD pipelines using GitHub Actions, Jenkins, or similar tools.
• Implement infrastructure-as-code using AWS CDK, Terraform, or CloudFormation.
• Collaborate with cross-functional teams to deliver reliable, secure platform capabilities.
• Understand existing architectures quickly, contribute independently, and drive improvements.
• Support AI platform governance and compliance.

Skills

MCP Server Management

MCP Observability

Python

AWS

Docker

GitHub Actions

Tools

AWS CloudFormation

Amazon CloudWatch

Job description

Role Description

We are seeking an experienced Senior MCP & Python Platform Engineer with strong expertise in MCP Server Management, MCP Observability, Python, and AWS to design, build, deploy, and operate production-grade AI services and platform components. The ideal candidate will have experience working with Model Context Protocol (MCP) implementations, cloud-native architectures on AWS, AI application integration patterns, and modern software engineering practices.

Key Responsibilities

• Design, develop, deploy, and maintain scalable platform services using Python.
• Manage and operate MCP Server Management capabilities for AI-powered applications and tool integrations.
• Implement and enhance MCP Observability practices, including monitoring, logging, tracing, and operational visibility for MCP-based services.
• Build and operate production services on AWS, leveraging cloud-native services and best practices.
• Design and integrate APIs and services that expose data, tools, and AI capabilities to client applications.
• Develop and support LLM-based application workflows, including retrieval-augmented generation (RAG), prompt orchestration, and tool integration patterns.
• Build and maintain containerized workloads using Docker.
• Create and support CI/CD pipelines using GitHub Actions, Jenkins, or similar tooling.
• Implement and manage infrastructure-as-code solutions using AWS CDK, Terraform, or CloudFormation.
• Collaborate with cross-functional teams to deliver reliable, secure, and scalable platform capabilities.
• Quickly understand existing architectures and codebases, contribute independently, and drive continuous improvements.
• Support AI platform governance, evaluation, compliance, and operational best practices.
• Contribute to the design and optimization of search, retrieval, and AI service integration capabilities where required.

Required Skills

Proficient

• MCP Server Management
• MCP Observability
• Python

Intermediate

• AWS

Experience

• 6+ years of professional experience in software, data, or AI/ML engineering.
• 3+ years of direct experience building and operating production services on AWS.

Skills

AWS, AWS CloudFormation, Amazon CloudWatch