AI / ML Lead

About the Company

Global consulting and technology company focused on delivering operational excellence to the insurance industry. It provides strategic solutions across underwriting, claims, analytics, and digital transformation to help insurers improve efficiency and scalability.

About the Role

Lead the design and deployment of enterprise-grade generative AI systems, driving innovation in LLM orchestration, multimodal architectures, and scalable AI / ML pipelines. Own the full lifecycle from research to production, ensuring alignment with business objectives and ethical AI standards. This will be a hands-on individual contributor role as well as providing technical guidance to junior developers.

Job Location- Noida / Gurgaon / Pune and Bangalore

Key Responsibilities

Technical Leadership

Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for cost-performance optimization.

Design GPU / TPU-optimized training pipelines (FSDP, DeepSpeed) for billion-parameter models.

Cloud-Native AI Development

Build multi-cloud GenAI platforms (Azure OpenAI + GCP Vertex AI + AWS Bedrock) with unified MLOps.

Implement enterprise security : VPC peering, private model endpoints, and data residency compliance.

Innovation & Strategy

Pioneer GenAI use cases : Agentic workflows, AI-driven synthetic data generation, real-time fine-tuning.

Establish AI governance frameworks : Model cards, drift monitoring, and red-teaming protocols.

Cross-Functional Impact

Partner with leadership to define AI roadmaps and ROI metrics (e.g., $ saved via AI-driven automation).

Mentor junior engineers and evangelize GenAI best practices across the organization.

Qualifications

Education : Bachelors / Masters in CS / AI or equivalent industry experience (5+ years in ML, 2+ in GenAI).

Technical Mastery : Languages : Python.

Frameworks : Expert-level PyTorch, TensorFlow Extended (TFX), ONNX Runtime.

Cloud : Certified in Azure AI Engineer Expert and / or GCP Professional ML Engineer.

GenAI Expertise :

Shipped production GenAI systems (e.g., 10k+ QPS chatbots, code autocomplete at GitHub Copilot scale).

Advanced prompt / response engineering : Self-critique chains, LLM cascades, guardrail-driven generation.

Required Skills

Must-Have Experience :

Cloud AI experience :

Azure : Designed solutions with Azure OpenAI, MLOps Pipelines, and Cognitive Search.

GCP : Scaled Vertex AI LLM Evaluation, Gemini Multimodal, and TPU v5 Pods.

High-Impact Projects :

Automation projects to reduce significant $$ costs.

Brought RAG systems with hybrid search (vector + lexical) and dynamic data hydration.

Led AI compliance for regulated industries (healthcare, finance).

Preferred Skills

Certifications :

Azure : Microsoft Certified : Azure AI Engineer Associate.

GCP : Google Cloud Professional Machine Learning Engineer.

Experience with hybrid / multi-cloud GenAI deployments (e.g., training on GCP TPUs, serving via Azure endpoints).