Mission :

Head the AI engineering charter for Newgens ECM platform (NewgenONE OmniDocs) by building, scaling, and governing AI/GenAI capabilities that power intelligent capture, classification, search, insights, and document generation across content-centric workflows. Lead a high-performance team of AI/ML engineers and data scientists to transform. The goal is to scale the Agentic AI capabilities, enabling autonomous decision-making, hyper-accurate intelligent document processing (IDP), and Generative AI-driven content discovery for our global clients in highly regulated industries.

Key Outcomes & Responsibilities :

- AI Strategy & Roadmap : Define the technical AI vision for the ECM portfolio, focusing on the transition from traditional OCR/Extraction to LLM-powered cognitive understanding and Agentic AI for document-heavy workflows.

- Architect multi-tenant, cost-efficient GenAI services (prompt orchestration, retrieval-augmented generation, evaluation harnesses, guardrails) consumable across WorkDesk, IDP, and Content Management surfaces.

- Advance document intelligence : combine LLMs with layout understanding, OCR/ICR/OMR/MICR, and computer vision; expand pre-trained templates and Model Training Studio for continuous learning on new document types.

- Ship next-gen enterprise search (semantic + hybrid vector), relevance tuning, and cross-repository federation; enable context-aware retrieval in ECM workflows.

- Governance & Ethical AI : Establish frameworks for "Explainable AI" to ensure that automated decisions within the ECM platform are auditable, transparent, and compliant with global data privacy regulations (GDPR, SOC2, etc.).

- Establish robust MLOps : data curation/labelling, training/validation, bias & safety testing, model registry, blue/green and canary rollouts, telemetry, and cost governance across clouds.

- Build, mentor and lead a high-performing team (applied scientists, ML engineers, platform engineers, data/ops, evaluation & safety) with strong engineering and scientific rigor.

Qualifications :

- 10+ years of experience in AI/ML with a demonstrable track record of shipping production AI; leadership experience managing AI/ML engineering teams.

- Depth in document & language AI : LLMs (prompting, fine-tuning, RAG), information retrieval (BM25, vector search, hybrid ranking), computer vision for documents, and OCR/ICR/OMR/MICR.

- Architecture & MLOps : multi-tenant AI services, feature stores, model registries, CI/CD for ML, observability, and cost/performance optimization on Azure/AWS/GCP.

- Stakeholder leadership : partner with Product Management and GTM teams to define outcomes and articulate AI tradeoffs to customers, executives, and analysts.

- Excellent communication and storytelling skills for technical and non-technical audiences.

Indicative Tech Stack :

- AI/ML : PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex, ONNX/Triton;