Senior Technical Lead - Generative AI

Role overview

Compensation

• Salary range is INR 3,000,000 to INR 5,000,000 per annum, described as INR 30 to 50 LPA.

Workplace and employment

• The role is remote within India.
• The employment type is full-time.
• The posting requests 10+ years of experience.

AI architecture and development

• Architect and develop agentic AI and generative AI systems from concept through production.
• Build reasoning agents, tool or function-calling workflows, and multi-agent architectures using frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration.
• Design and productionize RAG pipelines involving chunking, embeddings, vector search, and hybrid retrieval.
• Evaluate foundation models using performance, accuracy, latency, cost, and business criteria.
• Develop prompt engineering, model routing, fine-tuning, and optimization strategies.

Production engineering

• Own architecture decisions for scalable, reliable, and cost-efficient LLM applications.
• Establish standards for testing, evaluation, observability, guardrails, hallucination mitigation, and production monitoring.
• Design APIs, microservices, and cloud-native architectures for AI applications at scale.
• Drive AI and LLMOps practices across model lifecycle management, deployment, monitoring, and continuous improvement.

Technical leadership

• Lead, mentor, and develop AI/ML and backend engineers.
• Conduct technical design reviews, architecture discussions, and code reviews.
• Establish engineering best practices and remain involved in complex engineering problems.

Collaboration

• Partner with Product, Data Science, Platform, Security, and Compliance teams to deliver business-aligned AI solutions.
• Ensure systems address privacy, security, compliance, and responsible-AI requirements.
• Communicate complex technical concepts to senior leadership and business stakeholders.
• Represent AI engineering in strategic GenAI technology and roadmap discussions.

Required qualifications

• 10+ years of software engineering experience, including 4+ years working directly with AI/ML systems.
• At least 2+ years of hands-on experience building and deploying LLM-based or agentic AI applications in production.
• Deep expertise in LLM development, RAG, embeddings, vector databases, prompt engineering, and AI agents.
• Strong Python and software engineering fundamentals with scalable, distributed systems experience.
• Experience with APIs, microservices, cloud-native architecture, and at least one major cloud platform.
• Experience with MLOps or LLMOps tools such as MLflow, LangSmith, Weights & Biases, or equivalents.
• Working knowledge of LLM fine-tuning and evaluation techniques, including LoRA or PEFT and RLHF concepts.
• Ability to lead technically, mentor engineers, own architecture decisions, and communicate with business stakeholders.

Preferred qualifications

• Experience with Llama or Mistral and other open-source models.
• Contributions to AI or GenAI open-source projects, technical publications, or conference presentations.
• Experience with regulated-industry AI solutions, guardrails, red-teaming, responsible AI, or model safety frameworks.
• Previous formal people-management experience.