Role: AI Data Engineer Function: Data Engineering / Applied AI
Type: Full-time
Industry: Information Technology & Services / Artificial Intelligence / Critical Infrastructure

The company is a research-first AI startup incubated at the Indian Institute of Science (IISc). It builds advanced AI for the planning and operations of critical networks.
Its core technology is a World Model that augments LLMs to reason about network state and dependencies, even with limited or noisy data. The founding team has raised over $100M across earlier ventures and published at leading AI research venues.
As AI Data Engineer, you will own the full data lifecycle — from raw, messy sources to model-ready inputs — that powers the company's AI products and agents. You will design, ship, and operate batch and streaming pipelines in production, not just prototypes. Working at the intersection of data engineering and applied AI, you will build the infrastructure that makes the company's models and agents reliable at scale.

Design, ship, and maintain batch and streaming pipelines that feed training, evaluation, RAG, and agent workflows end-to-end.
Extract structured data from PDFs, scanned documents, web pages, APIs, and internal systems using LLM-based and classical extraction methods.
Define and enforce data quality: validation rules, schema checks, deduplication, anomaly detection, and extraction evals before data reaches users or models.
Build tools, data interfaces, and guardrails for AI agents; use coding agents to accelerate your own pipeline work.
Own production operations for pipelines you build — monitoring, alerting, retries, cost and latency tracking, and on-call response.




Manage embedding pipelines: chunking strategies, embedding generation, vector store indexing, and refresh cycles.
Collaborate with ML, product, and backend engineers to translate data requirements into reliable, documented systems.

B.Tech / B.E. / Tech in Computer Science or a related field from an IIT or NIT/BITs.

- 2–3 years of hands-on experience building and shipping data pipelines to production — not just notebooks or prototypes.
- Strong Python and SQL, applied to real production data systems.
- Hands-on experience with LLM APIs for extraction, classification, or transformation, including prompt design and structured outputs.
- Experience building or working with AI agents — tool calling, agent frameworks, or agent-driven workflows.
- Demonstrated ownership of data quality in live systems: validation, testing, and debugging bad data.

Experience with vector databases and RAG pipelines.
Document AI or OCR work — layout parsing, table extraction, or multimodal models.
Building LLM evaluation sets or human-in-the-loop review workflows.
Data tooling such as dbt, Great Expectations, Spark, or DuckDB.
Prior experience at an early-stage or quick-moving startup.

Early ownership at a seed-stage, research-first AI company incubated at IISc — with real influence over technical direction.
Work on frontier AI problems at the intersection of LLMs, agents, and critical network infrastructure.
Collaborate directly with a founding team that has raised $100M+ and published at leading AI venues.
Lean, high-trust environment where your work ships to production and has measurable impact from day one.

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