We are looking for a mid-level AI engineer who is genuinely sharp, deeply grounded in AI, and has professional work to show for it.

Build production AI agents, workflows and document-intelligence systems for enterprise clients. This is deep, accuracy-critical delivery work, not building basic chatbots.

Experience: Atleast 2 years in AI/ML engineering.

Strong general software engineering: Python, APIs, clean production code, version control, testing.
Document & multimodal AI
Structured extraction under accuracy constraints: constrained/schema-based generation, validation, confidence scoring, and human-in-the-loop where it matters.
Evaluation & reliability: can build eval sets, measure accuracy, catch regressions, trace and debug failures in production.
Agentic/LLM system design: multi-step orchestration, tool calling, retries and fallbacks — with the judgment to use plain deterministic code when an agent isn't warranted.

Background — good to have

Retrieval systems beyond basic RAG: hybrid retrieval, reranking, entity resolution, and graph/relational modeling.
Enterprise integration: SAP/Oracle or other ERP/procurement systems, on-prem/VPC deployments, and working within client security and legacy-data constraints.
Manufacturing, supply-chain, procurement, or industrial domain exposure.
Fine-tuning experience and cost/latency optimization (knowing when classical CV/OCR beats an LLM, when to fine-tune vs prompt).
Forward-deployed / client-facing delivery experience — comfortable sitting with a client, scoping the problem on ambiguous data.
Familiarity with AI-native coding tools (Claude Code, Cursor, etc.).

AI Engineer