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Senior AI Automation Engineer

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Onsite

Senior AI Automation Engineer

Mukizh Fashions

Senior AI Automation Engineer

Skills

SQL QueriesData EngineeringDockerDjangoFlaskPythonC#.NETMicroservicesPostgreSQLRedisAIAWSFastAPIAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Tamil Nadu, India

Work mode:

Onsite

Published on:

30 September 2026

What they need


Role Overview

We are looking for a Senior AI Automation Engineer to design, develop, and deploy enterprise-grade AI automation solutions for the Healthcare and Revenue Cycle Management (RCM) domain.

The ideal candidate should have strong expertise in Python backend development, Generative AI, AI Agent frameworks, RAG, LLM integration, workflow orchestration, cloud-native architecture, and enterprise system integrations.

The role will involve building scalable AI-powered applications, integrating AI capabilities with existing enterprise platforms, implementing AI Ops practices, and mentoring engineering teams.

Key ResponsibilitiesAI & Automation

  • Design and develop enterprise-grade Generative AI and AI Agent solutions.
  • Build AI-powered workflows for RCM, claims, enrollment, eligibility, payer/provider integrations, and document automation.
  • Develop solutions using modern AI Agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent.
  • Integrate LLMs using Amazon Bedrock, OpenAI, Azure OpenAI, or similar platforms.
  • Design and implement RAG architectures, prompt engineering, guardrails, and AI evaluation frameworks.
  • Work with MCP (Model Context Protocol) and modern AI tooling/skills.

Backend Engineering

  • Build scalable and production-grade Python backend services.
  • Develop REST APIs, WebSockets, asynchronous processing, and microservices.
  • Use FastAPI, Flask, or Django for backend development.
  • Design stateful/stateless and event-driven architectures.
  • Integrate Python applications with C#/.NET applications, enterprise platforms, and external APIs.
  • Design and implement secure and scalable backend services.

Workflow Orchestration

  • Design and implement long-running business workflows using Temporal or equivalent workflow orchestration platforms.
  • Develop reliable, fault-tolerant, and scalable workflow processes.
  • Implement event-driven patterns and asynchronous processing.

Security

  • Implement authentication and authorization using:
  • OAuth2
  • JWT
  • SSO
  • RBAC / ABAC
  • Apply API security best practices.
  • Implement secure secrets management and access controls.

Cloud & AI Operations

  • Deploy and manage AI applications on AWS or Azure.
  • Containerize applications using Docker.
  • Implement CI/CD pipelines and production deployment processes.
  • Implement AI Ops, monitoring, observability, logging, and model monitoring.
  • Support model lifecycle management, evaluation, and production troubleshooting.

Database & Data Engineering

  • Work with relational and NoSQL databases.
  • Develop and optimize SQL queries.
  • Work with:
  • SQL Server
  • PostgreSQL
  • Redshift
  • Redis
  • NoSQL databases
  • Vector databases such as Pinecone, ChromaDB, pgvector

Engineering Leadership

  • Drive coding standards, architecture practices, documentation, and CI/CD best practices.
  • Conduct code reviews and provide technical guidance to engineering teams.
  • Mentor junior and mid-level engineers.
  • Collaborate with product, business, architecture, and cross-functional teams.
  • Troubleshoot complex production and integration issues.

Required SkillsCore

  • 5+ years of relevant software engineering experience.
  • Expert-level Python development.
  • Strong experience with FastAPI, Flask, or Django.
  • Strong understanding of REST APIs, WebSockets, asynchronous programming, and microservices.
  • Experience with SQL and enterprise database systems.

Generative AI & Agents

  • Generative AI / LLM application development.
  • AI Agent frameworks such as:
  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • Equivalent frameworks
  • RAG architecture and implementation.
  • LLM integration with Amazon Bedrock, OpenAI, Azure OpenAI, or similar.
  • Prompt engineering and AI guardrails.
  • Vector databases.
  • MCP (Model Context Protocol) and AI tooling knowledge.

Cloud & DevOps

  • AWS preferred; Azure also acceptable.
  • Docker.
  • Git.
  • CI/CD pipelines.
  • Monitoring, logging, observability, and production support.

Security

  • OAuth2
  • JWT
  • SSO
  • RBAC / ABAC
  • API security
  • Secrets management

Integration

  • Experience integrating Python services with C#/.NET applications.
  • Experience working with enterprise APIs and third-party integrations.

Preferred Qualifications

  • Experience building enterprise-grade AI automation platforms.
  • Healthcare / RCM domain experience.
  • Knowledge of Claims, Eligibility, Enrollment, Prior Authorization, and Payer/Provider workflows.
  • Strong understanding of distributed systems and scalable backend architecture.
  • Experience integrating AI solutions into existing enterprise applications.
  • Strong debugging, architecture, and problem-solving skills.
  • Experience leading technical teams and mentoring engineers.
  • Experience delivering production-grade Full Stack AI applications.

Pay: Up to ₹180,000.00 per month

Work Location: In person

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