Quantiphi
Website:
quantiphi.com
Job details:
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!
Click on Apply to know more.