Senior Technical Lead - Agentic / Generative AI - Remote

Hiring for: A US-based AI/ML technology company working with enterprise customers globally.

Role: Senior Technical Lead - Agentic AI / Generative AI - Remote

Positions: 1

Experience: 10 to 15 years

Location(s): Remote (Global)

Type: Remote / Permanent

Salary: Upto 85 LPA (best as per the fitment)

Notice Period: Immediate to 30 days

We're looking for a Senior Technical Lead to own the architecture and delivery of our Agentic AI / Generative AI initiatives from early prototyping through production deployment at scale. This is a hands-on leadership role: you'll design and build LLM-powered agent systems yourself while also setting technical direction and mentoring a small team of AI/ML engineers. You'll work closely with product, data, and platform teams to turn GenAI capability into real, reliable, production-grade systems - not just demos.

Roles and Responsibilities:

• Architect and lead development of agentic AI systems: multi-step reasoning agents, tool-use/function-calling pipelines, and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or custom agent orchestration)
• Design and productionize Retrieval-Augmented Generation (RAG) pipelines, including chunking strategy, embeddings, vector search, and hybrid retrieval.
• Lead evaluation and selection of foundation models (proprietary and open-source) and drive prompt engineering, fine-tuning, and model-routing strategy across use cases.
• Own technical architecture decisions for scalability, latency, cost, and reliability of LLM-based systems in production.
• Set and enforce engineering standards for testing, evaluation (offline/online), guardrails, hallucination mitigation, and observability of agentic systems.
• Lead, mentor, and grow a team of AI/ML/backend engineers - run technical design reviews, code reviews, and career development.
• Partner with Product, Data Science, Security, and Compliance to ensure GenAI systems meet privacy, security, and responsible-AI requirements.
• Stay current with the fast-moving GenAI/agentic landscape and translate relevant advances into the team's roadmap.
• Represent the AI engineering function in cross-functional discussions on GenAI strategy and roadmap.

Required Skills:

• 10+ years of overall software engineering experience, including 4+ years working directly with ML/AI systems and 2+ years specifically building and shipping LLM-based or agentic AI applications in production.
• Deep hands-on experience with LLM application development: prompt engineering, RAG architectures, vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector), and embeddings.
• Practical experience building multi-agent or tool-using AI systems (agent orchestration frameworks, function/tool calling, memory management, planning/reasoning loops).
• Strong software engineering fundamentals: Python required; experience designing scalable, distributed, production systems (APIs, microservices, cloud-native architecture).
• Experience with at least one major cloud platform (AWS, Azure, or GCP) and MLOps/LLMOps tooling (e.g., MLflow, LangSmith, Weights & Biases, or equivalent).
• Working knowledge of fine-tuning and evaluation techniques for LLMs (e.g., LoRA/PEFT, RLHF concepts, offline/online evaluation frameworks).
• Demonstrated experience leading or mentoring engineers: technical leadership, design ownership, and cross-team collaboration, even without a formal people-management title.
• Strong communication skills: able to translate between deep technical detail and business/executive stakeholders.

Preferred:

• Experience with open-source LLM deployment and fine-tuning (Llama, Mistral, etc.) alongside proprietary APIs (OpenAI, Anthropic, Gemini).
• Contributions to GenAI/agentic open-source projects, technical publications, or conference talks.
• Experience building AI systems in enterprise environments with complex privacy, security, compliance, or governance requirements.
• Experience with model guardrails, red-teaming, or AI safety/evaluation frameworks.
• Prior experience formally managing a team of engineers (not just technical leadership).

NOTE: This role offers an opportunity to take ownership of architecture and delivery for Agentic AI initiatives, influence technical direction, and mentor a growing team while working on production-scale GenAI systems.