Lead Data Engineer with AI experience

Ovii's Interpretation of the Role

Lead Data Engineer driving AI‑centric data pipelines, retrieval systems, and ML/LLM ops on cloud platforms. Own end‑to‑end data infrastructure that powers conversational agents, dashboards, and predictive models for enterprise AI products.

Role Snapshot

• Lead data engineering initiatives
• Design and operate production‑grade AI pipelines
• Build retrieval and vector‑store infrastructure
• Ensure data governance, security, and compliance
• Drive ML/LLM ops foundations
• Mentor engineering best practices

Must-Have Requirements

• Python
• SQL
• PySpark
• Kafka
• Snowflake/DataBricks
• Delta Lake
• AWS (S3, Glue, Kinesis, EKS, Redshift)
• Docker
• Kubernetes
• GitHub Actions
• data engineering
• cloud services
• AI/ML data infrastructure

Nice-to-Have Signals

• LangChain
• LlamaIndex
• LLM APIs (OpenAI, Bedrock, Claude, HuggingFace)
• Pinecone
• FAISS
• ChromaDB
• OpenSearch
• MLflow
• FastAPI
• Neo4j
• prompt engineering
• RLHF dataset preparation
• LLM fine‑tuning workflows
• vector store retrieval
• LLM fine‑tuning

Work Setup

• Location: India, India
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Salary range
• Visa sponsorship
• Remote eligibility details
• Travel requirements

What You'll Likely Work On

• Build, test, and maintain batch and real‑time data pipelines on Snowflake, PySpark, Delta Lake, and Kafka.
• Create end‑to‑end retrieval infrastructure, including document ingestion, embedding pipelines, and vector store management.
• Implement semantic layers, feature stores, and knowledge graphs to serve both ML models and LLM applications.
• Develop ML/LLM data pipelines, experiment tracking, dataset versioning, and automated evaluation for model quality.
• Provide data APIs, tool schemas, and agent observability for autonomous agents and conversational AI consumers.
• Enforce data governance, RBAC, PII masking, and audit logging to meet compliance and security standards.

Good Fit If You Have

• Enjoy building production‑grade pipelines at scale (batch & streaming).
• Comfort with cloud‑native data architectures on AWS/Azure.
• Interest in AI/LLM‑driven products and retrieval systems.
• Experience with data governance, quality frameworks, and compliance.
• Collaborative remote‑first mindset.