Skills:
Python Engineering, LLM Orchestration, Snowflake, Production Engineering, Vector Databases, SQL,

About The Role

We are looking for a Senior AI Engineer to take ownership of our most complex agentic workflows. In this role, you will bridge the gap between "cool demo" and "enterprise-grade reliability."

You wont just be prompting models; you will be architecting the orchestration layer that governs them. You will be responsible for the end-to-end lifecycle of our agents-from system design and prompt engineering to latency optimization, cost management, and rigorous evaluation frameworks. You will also mentor younger engineers and help define our AI engineering best practices.

Responsibilities

• Lead the architectural design of complex, multi-agent systems using LangGraph/LangChain that can handle long-running, asynchronous enterprise tasks.
• Own the "Evals": Design and build automated evaluation pipelines to measure agent accuracy, hallucination rates, and success metrics before deploying to production.
• Production Hardening: Optimize RAG pipelines for scale-tuning chunking strategies, retrieval algorithms, and vector search parameters for maximum relevance and speed.
• Cost & Latency Engineering: Make critical decisions on when to use massive foundation models (GPT-4) vs. smaller, specialized models to balance performance with unit economics.
• Collaborate with the Product Team to translate ambiguous business requirements ("Fix the ERP data") into concrete agentic behaviors and tool definitions.
• Mentor junior AI engineers, conducting code reviews and helping them level up their understanding of LLM application architecture.
  
  

Requirements

• 5+ years of total engineering experience, with significant recent focus on Applied AI / LLMs.
• Expert-level Python skills; you write clean, modular, and testable code.
• Deep production experience with LLM orchestration (LangChain, LangGraph, etc.) - you know where these frameworks break and how to fix them.
• Strong understanding of the modern Data Stack (SQL, Snowflake, Vector DBs); you know that good AI requires good data.
• Experience in MLOps or LLMOps (tracing, monitoring, and versioning prompts/chains).
• A pragmatic mindset: You know when to use a simple heuristic and when to deploy a complex agent.
  
  

Nice-to-Have Skills

• Experience fine-tuning open-source models (Llama, Mistral) for specific domain tasks.
• Background in traditional NLP or Machine Learning prior to the Generative AI boom.
• Experience with Kubeflow, Ray, or other distributed ML computing frameworks.
• Previous experience in a Founding Engineer or early-stage startup role.
  
  

Education & Certification

• We dont actually care about qualifications as long as you are a rockstar engineer who wants to keep learning and make a massive impact.
  
  

What We Offer

• A values-aligned culture: always learning mindset, collaborative environment, and an entrepreneurial approach to getting things done.
• Competitive, flexible salary based on experience.
• Equity via ESOPs.
• Leadership role shaping AI/LLM services at enterprise scale.
• Collaborative, high-energy startup culture in South Delhi and San Francisco.
• Access to top AI researchers worldwide to drive innovation and continuous learning.
• Flexible work-from-home days balanced with on-site collaboration.