Senior Technical Lead - Agentic AI / Generative AI

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Lead - Agentic AI / Generative AI based in India.

As a Senior Technical Lead, you will own the architecture, technical direction, and delivery of production-grade Agentic AI and Generative AI solutions. You will design and build LLM-powered applications, RAG architectures, multi-agent workflows, and intelligent systems that move from experimentation into scalable enterprise production. The role combines hands-on engineering with technical leadership, mentoring, and cross-functional collaboration. You will work closely with Product, Data, Platform, Security, and Compliance teams to turn emerging AI capabilities into reliable business solutions. You will establish engineering standards around evaluation, observability, security, guardrails, and responsible AI. This is an opportunity to shape AI engineering strategy while remaining deeply involved in complex technical challenges. You will play a key role in building scalable, secure, and business-ready AI capabilities in a fast-evolving technology environment.

Accountabilities:

• Architect, develop, and productionize Agentic AI and Generative AI solutions from early concepts and prototypes through scalable enterprise deployment.
• Design multi-step reasoning agents, tool and function-calling workflows, memory systems, planning mechanisms, and multi-agent architectures using frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration solutions.
• Design and implement scalable RAG pipelines covering document chunking, embeddings, vector search, hybrid retrieval, and retrieval optimization.
• Evaluate and select foundation models based on accuracy, performance, latency, cost, scalability, and business requirements.
• Develop and implement strategies for prompt engineering, model routing, fine-tuning, and model optimization.
• Own key technical architecture decisions for reliable, scalable, secure, and cost-efficient LLM applications.
• Establish engineering standards for testing, evaluation, observability, guardrails, hallucination mitigation, security, and production monitoring.
• Design APIs, microservices, and cloud-native architectures capable of supporting AI applications at scale.
• Drive AI/LLMOps practices across model lifecycle management, deployment, monitoring, evaluation, and continuous improvement.
• Lead, mentor, and develop AI/ML and backend engineers while fostering strong engineering standards and technical excellence.
• Conduct architecture reviews, technical design discussions, and code reviews, providing clear technical direction to the engineering team.
• Remain hands-on with complex engineering challenges and contribute directly to critical technical solutions.
• Collaborate with Product, Data Science, Platform, Security, and Compliance teams to align AI solutions with business objectives and organizational requirements.
• Ensure AI systems meet appropriate privacy, security, compliance, responsible-AI, and model-safety standards.
• Communicate complex AI and engineering concepts clearly to senior leaders, business stakeholders, and technical teams.
• Represent the AI engineering function in strategic technology discussions and GenAI roadmap decisions.

Requirements

• 10+ years of overall software engineering experience, including at least 4 years working directly with AI/ML systems.
• 2+ years of hands-on experience building and deploying LLM-based or agentic AI applications in production.
• Deep expertise in LLM application development, RAG, embeddings, vector databases, prompt engineering, and AI agents.
• Practical experience with multi-agent systems, tool/function calling, memory management, planning, and reasoning workflows.
• Strong Python skills and solid software engineering fundamentals, with experience building scalable, distributed, production-grade systems.
• Experience designing APIs, microservices, and cloud-native architectures.
• Hands-on experience with at least one major cloud platform, such as AWS, Azure, or GCP.
• Experience with MLOps or LLMOps platforms such as MLflow, LangSmith, Weights & Biases, or equivalent tools.
• Working knowledge of LLM fine-tuning and evaluation techniques, including LoRA/PEFT, RLHF concepts, and offline and online evaluation frameworks.
• Proven ability to make architecture decisions, provide technical leadership, mentor engineers, and drive engineering initiatives across teams.
• Strong communication and stakeholder-management skills, with the ability to translate complex technical concepts into clear business and executive-level discussions.
• Experience deploying or fine-tuning open-source models such as Llama or Mistral is an advantage.
• Contributions to AI or Generative AI open-source projects, technical publications, or conference presentations are a plus.
• Experience delivering AI solutions in regulated industries such as finance, healthcare, or telecommunications is desirable.
• Knowledge of AI guardrails, red-teaming, responsible AI, model safety, and evaluation frameworks is beneficial.
• Previous formal people-management experience is a plus.

Benefits

• Competitive annual compensation of approximately ₹30,00,000-₹50,00,000, based on experience and role fit.
• Fully remote working opportunity from India.
• Full-time employment.
• High-impact technical leadership role with significant ownership over AI architecture and engineering direction.
• Opportunity to work on production-grade Agentic AI and Generative AI systems.
• Exposure to advanced technologies including LLMs, RAG, multi-agent architectures, LLMOps, model evaluation, and AI safety.
• Opportunity to mentor and develop AI/ML and backend engineering talent.
• Cross-functional exposure to Product, Data, Platform, Security, and Compliance teams.
• Opportunity to shape enterprise AI strategy and technology roadmaps.
• Fast-evolving environment focused on innovation, scalability, and practical business impact.