AI/ML Engineer at dotSolved Systems in Chennai, Tamil Nadu, IN

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)