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AIML Engineer


Job Location:

Chennai - India

Monthly Salary: Not provided by the employer
Experience Required: 8years
Posted: 28 August 2026 (16 hours ago)
Application Deadline: 25 November 2026
Vacancies: 1 Vacancy

Job Summary

Position: AI/ML Engineer
Location: Chennai - Remote
Shift Timing: 3.00PM - 12.00AM IST

Build AI Systems (Core Responsibility)
  • Design and implement end-to-end AI/ML solutions including LLM-based applications
  • Build RAG pipelines using vector databases and enterprise data sources
  • Build machine learning models that automate their training validation monitoring and retraining
  • Develop APIs and services to operationalize AI capabilities across the organization

Develop Data AI Pipelines
  • Build ingestion for multi-modal content and transformation pipelines for structured and unstructured data
  • Integrate AI workflows with enterprise systems (policy claims billing etc.)
  • Ensure data quality traceability reliability and governance in all AI pipelines

Operationalize Models (MLOps)
  • Implement CI/CD for AI/ML workflows
  • Deploy monitor and maintain models in production
  • Manage model versioning performance monitoring and retraining processes

Build on AWS
  • Develop solutions using: Amazon SageMaker AWS Lambda S3 Glue EKS and related services
  • Contribute to evolving use of AWS Bedrock

Apply Responsible AI Practices
  • Implement guardrails for LLM-based systems (grounding validation safety)
  • Ensure secure handling of sensitive data (PII financial etc.)
  • Build systems aligned with enterprise governance and compliance standards

Qualifications:
Required
  • 10 years in software data engineering 5 years AI/ML engineering
  • Hands-on experience building production AI/ML systems
  • Experience with RAG pipelines LLMs or NLP-based systems
  • Experience with AWS Bedrock or similar GenAI platforms
  • Experience with data pipelines and distributed systems
  • Experience deploying and operating systems in AWS
  • Working knowledge of MLOps practices (CI/CD monitoring versioning)

Preferred
  • Experience with vector databases (Pinecone Weaviate etc.)
  • Experience in regulated industries (insurance finance healthcare)
  • Exposure to microservices and containerized environments (Docker Kubernetes)



Required Skills:

Position: AI/ML Engineer Location: Chennai - Remote Shift Timing: 3.00PM - 12.00AM IST Build AI Systems (Core Responsibility) Design and implement end-to-end AI/ML solutions including LLM-based applications Build RAG pipelines using vector databases and enterprise data sources Build machine learning models that automate their training validation monitoring and retraining Develop APIs and services to operationalize AI capabilities across the organization Develop Data AI Pipelines Build ingestion for multimodal content and transformation pipelines for structured and unstructured data Integrate AI workflows with enterprise systems (policy claims billing etc.) Ensure data quality traceability reliability and governance in all AI pipelines Operationalize Models (MLOps) Implement CI/CD for AI/ML workflows Deploy monitor and maintain models in production Manage model versioning performance monitoring and retraining processes Build on AWS Develop solutions using: Amazon SageMaker AWS Lambda S3 Glue EKS and related services Contribute to evolving use of AWS Bedrock Apply Responsible AI Practices Implement guardrails for LLM-based systems (grounding validation safety) Ensure secure handling of sensitive data (PII financial etc.) Build systems aligned with enterprise governance and compliance standards Qualifications: Required 10 years in software data engineering 5 years AI/ML engineering Hands-on experience building production AI/ML systems Experience with RAG pipelines LLMs or NLP-based systems Experience with AWS Bedrock or similar GenAI platforms Experience with data pipelines and distributed systems Experience deploying and operating systems in AWS Working knowledge of MLOps practices (CI/CD monitoring versioning) Preferred Experience with vector databases (Pinecone Weaviate etc.) Experience in regulated industries (insurance finance healthcare) Exposure to microservices and containerized environments (Docker Kubernetes)


Required Education:

Any Degree