The Role
Design and deploy production AI/ML systems, including LLM applications, RAG pipelines, automated model training, APIs, and multimodal data pipelines. Operationalize models with MLOps practices such as CI/CD, monitoring, versioning, and retraining. Build solutions on AWS using SageMaker, Lambda, S3, Glue, EKS, and Bedrock. Implement responsible AI guardrails, data governance, security, and compliance for sensitive enterprise data.
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 such as 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.
