While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role: Technical Architect - Machine Learning
Experience Level: 10+ Years
Work location: Mumbai, Bangalore & Trivandrum
Role & Responsibilities:
Design and architect multi-layered Agentic AI solutions using Azure AI Foundry and LLM Orchestration frameworks (e.g., LangGraph, Semantic Kernel).
Define the technical roadmap for "Plan-and-Execute" agentic loops, specifically for unstructured data extraction and autonomous system updates.
Lead model selection and evaluation strategies, comparing high-reasoning models like Claude 3.5 Sonnet with open-weight alternatives (Llama 3.1) for cost and performance optimization.
Establish enterprise-grade security and governance standards following the NIST AI RMF framework.
Architect "Human-in-the-Loop" (HITL) workflows to ensure high-accuracy outputs for mission-critical SAP integrations.
Design the high-level handoff protocol between agents for multi-step tasks
Establish the security architecture for agentic access to external vendor portals and third-party APIs using zero-trust principles.
Provide technical leadership to MLEs and Platform engineers to ensure architectural alignment across workstreams.
Skills expectation:
Expertise in LLM Orchestration patterns (ReAct, Chain-of-Thought, multi-agent collaboration).
Deep experience with Azure AI services, including AI Search, AI Foundry, and Azure OpenAI.
Strong background in software architecture, including microservices and event-driven patterns (Azure Service Bus)
Proficiency in Python, advanced prompt engineering and techniques ML frameworks (PyTorch, TensorFlow)
Experience with AI Governance, compliance, and risk mitigation strategies.
Proven experience in deploying and monitoring LLMs in a production environment.
Expertise in tool-calling functions for agents using Playwright or Selenium to navigate and extract data from vendor portals lacking native APIs.
Familiarity with containerization (Docker, Kubernetes) for ML model serving.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
