AI Systems Architect

1 day ago


Vijayawada, Andhra Pradesh, India beBeeDataScientist Full time US$ 1,00,000 - US$ 1,25,000
Job Title: AI Architect

This is a challenging role that requires architecting industrial-grade AI systems to turn unstructured data into auditable, evidence-linked decisions. The ideal candidate will have experience building production AI/ML or search systems and possess strong systems thinking and data modeling skills.

Key Responsibilities
  • Design multimodal Retrieval Augmentation Graphs (RAGs) over various data sources, including PDFs, CAD/vector drawings, incident reports, and regulations.
  • Implement hybrid retrieval with reranking to achieve high accuracy and efficiency.
  • Build domain embeddings for bilingual technical terminology and craft routing/prompting for audit-ready outputs.
  • Ingest and normalize heterogeneous data sources, including ERP/MES exports, legacy DBs, SharePoint, and IoT streams.
  • Ship 10k+ document-type ingestion with schema validation, redaction, and temporal versioning for regulatory drift.
  • Integrate external APIs and orchestrate ensemble decisioning with SLA < 10s.
Requirements
  • 7+ years of experience building production AI/ML or search systems.
  • Expertise in Python 3.11+, SQL, and strong systems thinking and data modeling.
  • Experience with RAG at scale, including vector DBs, BM25, rerankers, prompt/routing strategies, and evals.
  • MLOps/SRE skills, including versioning, canaries/A-B, drift detection, observability, cost/perf trade-offs.
Nice-to-Have Skills
  • Knowledge graphs and schema alignment/ontologies.
  • VL/Document AI and CAD/vector parsing.
  • Orchestration frameworks and FastAPI.
  • LLM fine-tuning/LoRA and retrieval-graded generation.
Interview Process
  1. Technical Screen (45m): Live triage of a retrieval accuracy issue.
  2. System Design (2h): End-to-end design for a compliance-grade knowledge system.
  3. Take-Home Challenge: Build a working RAG system that processes safety documents in Korean and English.
  4. Founder Conversation: Vision/values alignment and references with prior enterprise clients.


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