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Salary
$38k – $84k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Architect · 12+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Fractal is a global artificial intelligence and analytics firm headquartered in New York, United States, and founded in 2000. The company provides enterprise AI solutions, decision intelligence services, and specialized products like Crux Intelligence and Eugenie.ai to help organizations scale their AI capabilities. It operates across 10 countries, serving Fortune 500 companies in sectors such as consumer packaged goods, retail, financial services, and healthcare.

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

AI Platform Architect: Agentic & Generative AI - Cogentiq

AboutCogentiq (Fractal’s Agentic AI Platform): Cogentiq is Fractal’s secure, scalable, enterprise agentic AI platform that enables teams to build, test, deploy, monitor agents and multi-agent workflows with strong observability, evaluation, guardrails and RBAC across any cloud or LLM framework. It includes a no/low-code development console, Agent & MCP Gateways, and an enterprise marketplace for reusable agents, tools, connections and guardrails.

Role Overview

As an AI Platform Architect, you will design and scale enterprise-grade Agentic AI and Generative AI platforms that power copilots, autonomous workflows, and multi-agent systems. This is a hands-on architect role for a builder who combines deep distributed-systems thinking with practical expertise in LLMs, agent orchestration, and cloud-native platforms.

You will define reference architectures, engineering standards, and core platform capabilities that enable teams to build, deploy, and operate AI systems at scale.

Key Responsibilities

Platform & Architecture Leadership

  • Architect scalable Agentic AI platforms supporting multi-agent orchestration, tool usage, memory, planning, and reasoning workflows
  • Design end-to-end GenAI platforms, including:
    • Prompt orchestration
    • Retrieval-Augmented Generation (RAG) pipelines
    • Vector databases
    • LLM integrations
  • Define modular, microservices-based, API-first architectures enabling rapid development of AI copilots and autonomous systems

Agentic & GenAI Systems

  • Define architectural patterns for:
    • Agent orchestration and coordination
    • Planning, reflection, and reasoning loops
    • Human-in-the-loop and feedback-driven systems
  • Evaluate and integrate emerging frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, and related ecosystems into enterprise platforms

Production Readiness & Reliability

  • Ensure production-grade reliability across AI platforms, including:
    • Observability and monitoring
    • Evaluation and experimentation frameworks
    • Guardrails, safety, and governance
    • Cost optimization for LLM-based systems
  • Lead architecture across LLMOps, MLOps, and platform operations

Cloud, DevOps & Infrastructure

  • Drive cloud-native platform architecture using AWS, Azure, or GCP
  • Lead Kubernetes-based deployments, CI/CD pipelines, and Infrastructure as Code (IaC)
  • Ensure scalability, security, and resilience of AI workloads

Collaboration & Technical Leadership

  • Partner with data science, product, and business teams to translate AI use cases into robust platform capabilities
  • Mentor senior engineers and architects; set engineering standards, reference architectures, and best practices
  • Act as a technical thought leader for enterprise AI platform strategy

Required Skills & Experience

  • 12-15 years of experience in platform engineering / architecture, with strong depth in distributed systems
  • Deep expertise in cloud platforms (AWS / Azure / GCP) and Kubernetes-based architectures
  • Hands-on experience with LLMs, RAG architectures, and vector databases (e.g., Pinecone, FAISS, Weaviate)
  • Strong understanding of agentic frameworks, multi-agent systems, and orchestration patterns
  • Experience across LLMOps / MLOps, including:
    • Model deployment
    • Monitoring and evaluation
    • Lifecycle and version management
  • Proficiency in microservices, APIs, event-driven systems, and scalable backend engineering
  • Strong coding experience in Python / Java / Go, with system-design depth
  • Experience working with data platforms (real-time + batch, large-scale data processing)
  • Solid understanding of AI safety, governance, and responsible AI frameworks

Good to Have

  • Experience building enterprise AI copilots or autonomous workflows
  • Exposure to reasoning frameworks, chain-of-thought orchestration, and agent memory systems
  • Prior consulting or client-facing experience leading AI-driven transformations

What We’re Looking For

A builder-architect who combines deep engineering rigor with a strong grasp of Agentic and Generative AI -someone who can turn cutting-edge AI concepts into scalable, secure, and production-ready enterprise platforms.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Hiring Related Queries

India: [email protected]

Outside India: [email protected]

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