AI Lead – Agentic AI Systems

About the Role

We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems.

Key Responsibilities

• Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines.
• Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design.
• Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral).
• Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT).
• Drive inference optimization using quantization, ONNX, TensorRT, and related tools.
• Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems.
• Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning.
• Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations.
• Integrate guardrails, content filtering, and data privacy best practices into GenAI systems.
• Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models).
• Oversee synthetic data generation for fine-tuning in low-resource domains.
• Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration.
• Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization.
• Translate cutting-edge AI research into usable product capabilities, from prototyping to production.
• Mentor and grow the AI team, establishing R&D best practices and benchmarks.
• Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve.

Required Skills & Expertise

AI & ML Foundations:
Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition

Ecosystem & Frameworks:
Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc.

Fine-tuning & Inference:
LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM

Data & Retrieval Systems:
FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs

MLOps & Evaluation:
Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination)

Security & Governance:
Content moderation, data privacy, model alignment, ethical constraints

Deployment & Ops:
Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes

Other:
Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery

Preferred Qualifications

• 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity
• Proven experience deploying LLM-powered systems at scale
• Experience working with cross-functional product and infrastructure teams
• Contributions to open-source AI projects or published research papers (a plus)
• Strong communication skills to articulate complex AI concepts to diverse stakeholders

Why Join Us?

• Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems
• Lead a passionate team of engineers and researchers
• Shape the future of ethical, explainable, and usable AI products

Ready to shape the next wave of AI? Apply now and join us on this journey!

Job Type: Full-time

Pay: ₹2,000,000.01 - ₹3,002,234.14 per year

Benefits:

• Flexible schedule
• Health insurance
• Paid time off
• Provident Fund

Schedule:

• Day shift
• Monday to Friday

Supplemental Pay:

• Yearly bonus

Work Location: In person