Data & AI Engineer

Innova Solutions

4 years

0 Lacs

pune maharashtra india

Posted:3 days ago| Platform:

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Skills Required

data ai engineering sql migration automation reconciliation tooling verification checks design retrieval orchestration graphs evaluation regression support containerization contracts etl azure openai stack storage ml docker testing integration oracle tuning controls workflow parsing json

Work Mode

Remote

Job Type

Full Time

Job Description

Data & AI Engineer

Location: Pune/Gurgaon/Remote

Role summary

Data & AI Engineer with a strong AI engineering focus to build agentic data workflows, evaluations, and observability for the client POC. Work spans Oracle→Azure SQL migration automation, data quality and reconciliation, and building reliable LLM/agent integrations and tooling on Azure.

Key responsibilities

Implement data migration jobs, verification, and reconciliation for Oracle→Azure SQL
Build data quality checks and performance validation for migrated workloads
Design and implement LLM-augmented data tasks and agents (tool use, retrieval, routing)
Develop orchestration graphs and agent workflows using LangGraph or similar
Implement retrieval pipelines with vector stores and structured search over SQL
Build evaluation harnesses for workflows and prompts, with regression-safe metrics
Add tracing, telemetry, and guardrails for LLM calls, tools, and data access
Support containerization and Azure‑native rewrites with data contracts and schemas
Contribute to agent/tool interfaces for data tasks and observability
Write concise docs, runbooks, and ADRs supporting decisions and operations

Required experience

4+ years in data, backend, or platform engineering with strong Python
Solid SQL skills and experience with ETL/ELT, schema migration, and validation
AI engineering foundations: prompt design, tool/function calling, retrieval, agents
Orchestration frameworks: LangGraph preferred; familiarity with LangChain or similar
Vector databases and embeddings: Azure AI Search, pg-vector, Milvus, or equivalent
Evaluation and tracing: LangSmith, OpenAI Evals, RAGAS, DeepEval, or equivalent
Azure stack: Azure SQL, Storage, Azure AI/ML or AI Studio, Azure OpenAI
Containers and CI fundamentals: Docker, pipelines, artifact handling
Testing culture: unit/integration tests for tools, prompts, and workflows

Nice to have

Oracle migration experience and performance tuning on Azure SQL
Financial services domain exposure and data controls compliance
Graph-structured workflow design and multi-agent patterns
Structured output parsing and schema enforcement (Pydantic, JSON schema)
Feature stores or offline/online retrieval patterns

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