Posted:7 hours ago|
Platform:
On-site
Full Time
• Document AI C OCR (invoices, legal documents, resumes, plant drawings)
• LLM-based apps (RAG, copilots, intelligent search, summarization)
• API-first SaaS products and on-prem enterprise solutions
Role Summary
We’re looking for a hands-on Lead AI Engineer (6–10 years) who can:
• Lead design and delivery of LLM G Document AI solutions end-to-end
• Own AI services in production (APIs, pipelines, monitoring)
• Mentor a team of AI engineers and work directly with clients (US C India)
This is a technical leadership role, not a pure manager role.
Key Responsibilities
• Own the end-to-end lifecycle of AI features – from requirement understanding
and solution design to development, deployment and monitoring.
• Build LLM/RAG-based solutions using vector databases (e.g., pgvector, FAISS,
Chroma, OpenSearch) for search, ǪCA, extraction and summarization over
documents.
• Develop Document AI models / pipelines for OCR post-processing, entity/key–
value extraction, classification and layout/table understanding.
• Deploy models as scalable APIs / microservices in cloud and on-prem
environments using Python, Docker and CI/CD.
• Work directly with client stakeholders to refine requirements, present solutions
and handle reviews / clarifications.
• Act as technical lead on 2–3 AI projects, guide the team on architecture, design
and best practices.
• Mentor junior ML engineers via code reviews, design discussions and technical
coaching.
• Design with security, privacy and cost in mind, especially for data-sensitive
domains (BFSI, healthcare, legal, HR).
Must-Have Requirements
Experience
• 6–10 years total experience, including 4+ years in AI / DL / NLP in production
environments.
• Proven experience taking AI solutions from PoC to production (not just
notebooks).
• Strong in Python and core CS fundamentals (data structures, algorithms, clean
code).
• Hands-on with AI / NLP / LLMs – classification, NER, ǪA, summarization,
document understanding.
• Experience with some of: PyTorch / TensorFlow / Hugging Face / LangChain /
LlamaIndex / spaCy.
• Built and deployed RESTful ML services / APIs integrated with web or mobile
applications.
• Worked with Docker and CI/CD pipelines; experience of AWS or GCP.
• Good SǪL skills and experience with at least one RDBMS (PostgreSǪL/MySǪL).
• Understanding of MLOps in production – monitoring, logging, model versioning,
rollback, performance C cost optimisation.
technical stakeholders.
• Comfortable interacting with international clients and leading requirement /
review calls.
• Strong ownership mindset and ability to lead and mentor junior engineers.
• Willingness to work with partial US time-zone overlaps for key meetings
when required.
Good-to-Have
• Experience in Logistics, Legal, HR/Recruitment, Healthcare, BFSI, Education,
Engineering/Plant drawings.
• Exposure to Vision Transformers / advanced CV for document layout and OCR
enhancement.
• Experience with experiment tracking tools (MLflow, DVC, WCB, etc.).
• Exposure to security G compliance (CIS, SOC2, GDPR, HIPAA, PCI-DSS, ITIL).
• Experience with on-prem / VPC-isolated deployments and data-sensitive
environments.
• Knowledge of a systems language (Go / Rust / C++ / Scala) is a plus, not
mandatory.
• Bachelor’s degree in Computer Science / Engineering / related
field (mandatory).
• Master’s degree is a plus.
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