Solutions Architect - Platform Engineer(Agentic AI)

About the Company: Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Company Highlights:

• Quantiphi, an AI-First Digital Engineering Services & Platforms company, with a 2.5x growth YoY since its inception in 2013
• Headquartered in Boston, with 3700+ professionals across global offices
• Winner of 3X NVIDIA AI Partner of the year award
• Winner of the 13X Google Cloud Partner of the Year award including "Machine Learning, Breakthrough and Social Impact partner
• Winner of 3X AWS AI/ML Partner of the Year award
• Preferred and Premier Partner for AWS, Google Cloud, NVIDIA, Snowflake, Databricks and more.

Visit us at : https://quantiphi.com/

Role: Solution Architect - Platform

Experience Level: 810 Years

Location: Bangalore/Chennai

Overview

We are seeking a highly experienced and visionary Solution Architect - Platform with a deep expertise in Agentic AI and system design to lead our technical strategy. You will play a pivotal role in developing the architectural blueprint and ensuring technical governance across our next-generation AI platforms. This role demands a high level of conceptual understanding, attention to detail, and the ability to translate complex research into production-ready assets. You will collaborate extensively with Verizon leadership to define technical roadmaps while serving as the final technical escalation point for the engineering team.

Roles and Responsibilities

• Solution Architecture & Governance: Lead the development of comprehensive solution architectures and establish stringent technical governance to ensure all implementations meet performance and security standards.
• Architectural Oversight: Review and approve all major architectural changes, ensuring alignment with long-term platform goals and scalability requirements.
• LLM Gateway Integration: Provide expert oversight on LLM gateway integration, focusing on secure, efficient, and scalable access to large language models.
• Production Readiness & Standards: Ensure the platform adheres to high standards of observability, auditability, and production readiness, implementing robust monitoring and logging frameworks.
• Leadership Collaboration: Partner with Verizon Leaders to create High-Level Designs (HLD), Low-Level Designs (LLD), and long-term technical roadmaps.
• Stakeholder Management: Provide daily status updates to leadership on project milestones, technical hurdles, and delivery timelines.
• Technical Escalation: Act as the final technical escalation point to resolve complex platform issues and architectural bottlenecks.
• Research & Development: Lead R&D initiatives on the latest trends in Agentic AI, translating cutting-edge research into tangible, reusable platform assets.

Skill Set Needed

• Agentic Frameworks: Proven experience with LangChain and DSPy for building complex, autonomous AI agents.
• LLM Tools & Protocols: Hands-on expertise with LiteLLM, Model Context Protocol (MCP), and Agent-to-Agent (A2A) communication patterns.
• Advanced System Design: Expert-level skills in System Design and API Governance for large-scale distributed platforms.
• Programming Proficiency: Advanced proficiency in Python, including FastAPI for high-performance API development and Pydantic for rigorous schema validation.
• Data Infrastructure: Experience with Redis and Vector DB interfaces (e.g., Pinecone, Milvus, or Weaviate) for efficient data retrieval and memory management.
• Infrastructure as Code (IaC): Practical experience with Terraform or Ansible to manage platform infrastructure.
• Kubernetes Mastery: Experience architecting and managing scalable applications using Kubernetes, including service mesh and resource management.
• Analytical Thinking: Exceptional problem-solving and critical thinking skills to tackle highly complex technical challenges.

Good to Have

• Experience with multi-cloud or hybrid cloud architectures (GCP, AWS, or Azure).
• Familiarity with MLOps tools beyond CI/CD, such as MLflow or DVC.
• Knowledge of security best practices, data governance, and compliance for AI workloads.
• Experience with performance and load testing using tools like Locust.
• Active contributions to the open-source community in the realm of Platform Engineering or AI.