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Senior Gen AI Engineer

2 weeks ago

Jamnagar, Gujarat, India beBeeAIENGINEER Full time ₹ 40,00,000 - ₹ 60,00,000
Gen AI Architect Position

We are seeking a skilled professional to take on the role of Gen AI architect. As a key member of our organization, you will be responsible for designing and implementing industrial-grade AI systems that transform data into actionable insights.

Key Responsibilities:
  • Design multimodal retrieval-augmented generation (RAG) systems that process heterogeneous data sources, including PDFs, CAD/vector drawings, incident reports, and regulations.
  • Implement hybrid retrieval algorithms, combining BM25 with dense, metadata, and knowledge graph features, to achieve ≥90% top-k answerability and traceable citations.
  • Build domain embeddings for bilingual technical terminology and craft routing/prompting strategies for audit-ready outputs.
  • Ingest and normalize diverse data sources, such as ERP/MES exports, legacy DBs, SharePoint, and IoT streams.
  • Develop a schema validation, redaction, and temporal versioning system for regulatory drift management.
  • Integrate external APIs, such as KOSHA, OSHA, and EPA, for finance modules like SEC/DART.
  • Orchestrate ensemble decisioning using rules, priors, and machine learning, with service-level agreements (SLAs) < 10 seconds; optimize large language model (LLM) flows for tool usage, caching, and distillation.
  • Operate on AWS EKS, Postgres, Pinecone, Temporal/Argo, Prometheus/Grafana, and CI/CD pipelines with test and evaluation gates.
  • Develop explanation layers, including attribution, chain-of-evidence, and human-in-the-loop feedback.
Requirements:
  • 7+ years of experience building production AI/ML or search systems, with 3+ enterprise deployments end-to-end.
  • Expert-level proficiency in Python 3.11+, SQL, and strong systems thinking and data modeling skills.
  • RAG expertise at scale, including vector databases (Pinecone/Weaviate/FAISS), BM25, rerankers, prompt/routing strategies, and evaluations (faithfulness, coverage, latency).
  • MLOps/SRE skills, including versioning, canaries/A-B testing, drift detection, observability, cost/performance trade-offs.
  • Excellent communication skills and ability to transform complex, multilingual data into reliable software solutions.
Preferred Qualifications:
  • Knowledge graph expertise, including Neo4j, RDF, and SPARQL.
  • Experience with visual language/document AI, CAD/vector parsing, and safety/compliance domain exposure.
  • Familiarity with orchestration frameworks (Temporal/Argo), FastAPI, AWS EKS, PostgreSQL, and Pinecone.
  • Skills in LLM fine-tuning, LoRA, retrieval-graded generation, and multi-agent planning.
Interview Process:
  1. Technical Screen (45m): Your RAG decisions and live triage of a retrieval accuracy issue.
  2. System Design (2h): End-to-end design for a compliance-grade knowledge system (data → RAG → UI/UX).
  3. Take-Home (48h window): See