3.0 - 8.0 years

9 - 19 Lacs

Noida, Gurugram

Work from Office

Job Title: Senior Generative AI Developer (Lead - Data Science) Gurgaon / Noida | 7-10 Years Experience About the Role We are looking for an experienced Senior Generative AI Developer to lead the design, development, and deployment of large-scale enterprise-grade GenAI systems. This is a hybrid role requiring both deep hands-on expertise and strategic leadership , working across multi-cloud environments and managing the full lifecycle of AI/ML systems. Key Responsibilities Technical Leadership Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for performance-cost optimization. Design and scale training pipelines using FSDP, DeepSpeed on GPU/TPU clusters. Cloud-Native AI Development Build and manage multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps. Implement enterprise-grade security: VPC peering, private endpoints , and regulatory compliance (e.g., data residency). Innovation & Strategy Drive pioneering initiatives such as Agentic workflows , real-time fine-tuning, and synthetic data generation . Define and execute AI governance : model cards, drift monitoring, red-teaming protocols. Cross-Functional Impact Collaborate with product and business teams to define GenAI strategy and ROI metrics (e.g., automation cost savings). Mentor junior engineers and promote GenAI best practices across the organization. Required Qualifications Education : Bachelors/Master’s in CS, AI/ML, or equivalent experience. Experience : 5+ years in ML, 2+ years specifically in Generative AI. Technical Mastery Languages : Expert in Python Frameworks : PyTorch, TensorFlow Extended (TFX), ONNX Runtime Certifications : Azure AI Engineer Expert, GCP ML Engineer (preferred) GenAI Expertise Experience shipping production-scale GenAI systems (e.g., 10k+ QPS chatbots, GitHub Copilot-scale models). Mastery of advanced LLM techniques (LLM orchestration, guardrails, self-reflective prompting). Must-Have Experience Azure : Azure OpenAI, MLOps Pipelines, Cognitive Search GCP : Vertex AI Evaluation, Gemini Multimodal, TPU v5 Pods Built RAG systems using hybrid search (vector + keyword) and real-time data hydration Led AI compliance in regulated domains (finance, healthcare) Preferred Additions Experience with multi-cloud GenAI deployments (e.g., training on GCP, serving on Azure). Certification in Azure and/or GCP AI tracks. Exposure to autonomous agents, vector databases , and AI-driven business automation.

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