Fractal
AI Platform Architect: Agentic & Generative AI - Cogentiq
Bengaluru · full-time
Company's own board12–15 yrs
First seen Sep 15 · seen live today · from Fractal's own Workday board
Skills mentioned
pythonjavagoawsazuregcpkubernetesdata sciencedevopsci/cd
The posting, as published
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
About Cogentiq (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: HiringsupportIndia@fractal.ai
Outside India: HiringsupportROW@fractal.ai
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