Senior Application Architect

Job Title:- GenAI Architect

Location:- Noida/Gurugram

What You’ll Own

• Lead all things GenAI — from LLM strategy and experimentation to production deployment and optimization.
• Lead the development of multi-agent systems that collaborate, reason, and learn.
• Design and own multi-agent LLM workflows, RAG pipelines, auto-evaluators, and structured generation.
• Work cross-functionally with product, backend, and infra teams to ship real AI features — not demos.
• Evaluate and integrate models (OpenAI, Claude, Mistral, local LLMs), and design robust prompting strategies.
• Build reusable systems for prompt versioning, model benchmarking, latency optimization, and failure handling.
• Mentor engineers in LLM application design

✅ You’ll thrive if you:

• Have 8+ years of engineering/ML experience, with 3+ years focused on GenAI/LLMs.
• Have led or architected LLM-heavy systems used in production (ideally customer-facing).
• Have built RAG systems, prompt chains, eval loops, or intelligent automation using LLMs.
• Experience in developing

  multi-agent systems

  and orchestration logic.
• Proficiency in Python and popular AI frameworks (e.g., LangChain, OpenAI, Hugging Face, AutoGen, etc.).
• Deep understanding of LLMs and how to adapt them to different tasks.
• Love shipping fast — but with depth, precision, and measurable quality.

Nice to Have:

• Experience with reinforcement learning or fine-tuning large models.
• Contributions to open-source AI/agent-related projects.

Key Responsibilities:

• Design, develop, and deploy advanced AI agents capable of handling complex tasks.
• Lead the development of multi-agent systems that collaborate, reason, and learn.
• Apply prompt engineering techniques to optimize LLM-based outputs for real-world applications.
• Collaborate cross-functionally to integrate AI solutions into larger systems and workflows.
• Perform backend/frontend/full stack development for sophisticated cloud applications
• Stay current with the latest developments in AI/ML, LLMs, agent frameworks, and research papers.
• Rapidly prototype and iterate on new ideas and agent capabilities.

Requirements:

• Demonstrated expertise in AI agent development, including hands-on experience building and running production-ready AI agents.
• Strong knowledge of prompt engineering principles and best practices.
• Proven track record of backend/frontend/full stack development
• Ability to work independently, solve ambiguous problems, and drive innovation.

Nice to Have:

• Experience with reinforcement learning or fine-tuning large models.
• Contributions to open-source AI/agent-related projects.
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).