The Role
Build and operate production AI/ML systems, including LLM applications, RAG pipelines, automated model training, APIs, multimodal data pipelines, and MLOps workflows. Deploy and monitor solutions on AWS using SageMaker, Lambda, S3, Glue, EKS, and Bedrock. Implement responsible AI guardrails, data governance, security, CI/CD, model versioning, performance monitoring, and retraining processes.
Summary Generated by Built 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)
Skills Required
- 10+ years of experience in software or data engineering
- 5 years of experience in 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 generative AI platforms
- Experience with data pipelines and distributed systems
- Experience deploying and operating systems in AWS
- Working knowledge of MLOps practices, including CI/CD, monitoring, and versioning
- Experience with vector databases such as Pinecone or Weaviate
- Experience in regulated industries such as insurance, finance, or healthcare
- Exposure to microservices and containerized environments, including Docker and Kubernetes
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The Company
What We Do
dotSolved, headquartered in Silicon Valley, provides business process automation, modern application engineering, and cloud infrastructure services. It helps small, medium, and large enterprises pursue digital transformation by defining, automating, and optimizing complex processes and engineering data- and analytics-driven applications. The company serves sectors including technology, energy, manufacturing, financial services, media, communications, retail, healthcare, and education, with experience in Big Data, ERP, and supply chain.
