AI Platform Architect: Agentic & Generative AI - Cogentiq

Fractal; India; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Fractal seeks a skilled AI Platform Architect to design and scale Agentic and Generative AI platforms. The role demands 12–15 years of experience in platform engineering, with deep expertise in cloud platforms like AWS, Azure, or GCP, as well as hands-on experience with large language models and distributed systems. The ideal candidate will lead architecture for AI systems, ensuring production readiness and reliability. Applicants should be builders-architects with a strong grasp of AI concepts and a passion for scalable solutions.

Qualifications

• 12–15 years of experience in platform engineering / architecture.
• Deep expertise in cloud platforms and Kubernetes-based architectures.
• Hands-on experience with LLMs and RAG architectures.

Responsibilities

• Design and scale enterprise-grade Agentic AI platforms.
• Lead architecture across LLMOps, MLOps, and platform operations.
• Drive cloud-native platform architecture using AWS, Azure, or GCP.

Skills

Platform engineering / architecture

Distributed systems

Cloud platforms (AWS / Azure / GCP)

Kubernetes

LLMs

Python

Tools

Pinecone

FAISS

Weaviate

Job description

**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 OverviewAs 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 ForA **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: [e-mail] India: [e-mail] inbox does not process resume submissions. All applications must be made through posted job openingsNot the right fit? Let us know you're interested in a future opportunity by clicking *Introduce Yourself* in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!