AI Transformation Specialist

5 days ago

Dindigul, Tamil Nadu, India beBeeArtificialIntelligence Full time ₹ 72,00,000 - ₹ 1,44,00,000

Role Summary

Transformative AI Expert
  • Design and implement large-scale, industrial-grade AI systems to drive business transformation. Convert diverse data sources into actionable insights to prevent accidents, ensure compliance, and enhance decision-making.
Key Responsibilities:
  1. Information Architecture & RAG Design
  • Develop multimodal Retrieval Augmentation Graphs (RAG) for PDFs, CAD drawings, MSDS/chemicals, and bilingual regulations.
  • Implement hybrid retrieval with reranking; target ≥90% top-k answerability and traceable citations.
  • Build domain embeddings for bilingual technical terminology and craft routing/prompting strategies for audit-ready outputs.
Industrial Data Ingestion & Pipelines
  • Ingest/normalize heterogeneous sources (ERP/MES exports, legacy DBs, SharePoint, IoT streams).
  • Ship 10k+ document-type ingestion with schema validation, redaction, and temporal versioning for regulatory drift.
  • Integrate external APIs (e.g., KOSHA, OSHA, EPA; for finance modules SEC/DART).
Production AI & MLOps
  • Orchestrate ensemble decisioning (rules + priors + ML) with SLA < 10s; cost-optimized LLM flows (tool-use, caching, distillation).
  • Operate on AWS EKS, Postgres, Pinecone, Temporal/Argo, Prometheus/Grafana; CI/CD with test & eval gates.
  • Build explanation layers (attribution, chain-of-evidence; SHAP/LIME where applicable) and human-in-the-loop feedback.
Vision & Document AI (Nice to have)
  • Table/figure/annotation extraction (LayoutLMv3/Donut/DocFormer), symbol detection (YOLOv8/RT-DETR), PDF vector parsing.
Client Collaboration
  • Lead deep-dive workshops with stakeholders; design Proof-of-Concepts that land transformative programs.
  • Mentor client teams and internal engineers; author crisp technical documents fit for audits.
Requirements:
  1. 7+ years building production AI/ML or search systems; 3+ enterprise deployments end-to-end.
  2. Expert Python 3.11+, SQL; strong systems thinking and data modeling.
  3. RAG at scale: vector DBs (Pinecone/Weaviate/FAISS), BM25, rerankers, prompt/routing strategies, evals (faithfulness, coverage, latency).
  4. MLOps/SRE: versioning, canaries/A-B, drift detection, observability, cost/perf trade-offs.
  5. Clear communication; ability to turn complex, multilingual data into reliable software solutions.
Nice-to-Have Skills:
  1. Knowledge graphs (Neo4j/RDF/SPARQL), schema alignment/ontologies.
  2. VL/Document AI (LayoutLMv3, Donut), CAD/vector parsing, safety/compliance domain exposure.
  3. Orchestration frameworks (Temporal/Argo), FastAPI, AWS EKS, PostgreSQL, Pinecone.
  4. LLM fine-tuning/LoRA, retrieval-graded generation, multi-agent planning.
Stack:

GPT-4o/GPT-4.1, Gemma-3 27B-VL, Qwen-VL, rerankers (Cohere/MXBAI), YOLOv8/RT-DETR, LayoutLMv3/DocFormer/Donut, FastAPI, Python, TypeScript, AWS EKS, Pinecone, Postgres, Temporal, Prometheus/Grafana.

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