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126 of 472 matching · page 3 of 3

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Agent infrastructureSeniorTop pickNew

Senior Platform Engineer: Agentic AI - Cogentiq

FractalBengaluru, Karnataka, India

Posted 1d ago/Full-time/Expires Nov 10, 2026

Apply on company site

Why it matters

The role owns production deployment of an enterprise agent platform, including MCP and agent gateways, multi-agent workflow orchestration, reusable connectors, observability, evaluation, guardrails, and governance. Engineers would build and troubleshoot customer-facing agent systems across runtime and integration layers.

About the job

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.

Platform Integration & Adoption Engineer – 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 Summary

As a Senior Platform Engineer – Agentic AI, you will play a critical role in integrating, deploying, and scaling Cogentiq, Fractal’s enterprise-grade agentic AI platform, across complex customer environments. You will enable production‑ready AI agent workflows by building deep integrations, deploying the platform across core, runtime, and governance layers, and driving adoption across engineering and business teams.

This role sits at the intersection of platform engineering, agentic systems, and enterprise integration.

Key Responsibilities

Platform Integration & Deployment

Integrate Cogentiq with enterprise ecosystems using MCP-based connectors, APIs, storage systems, and business applications (ERP, SaaS, internal tools)
Design and implement integrations using MCP Gateway, Agent Gateway, and Cogentiq SDKs
Deploy, configure, and operate Cogentiq across Core, Runtime (Kubernetes), and Governance layers
Set up and maintain CI/CD pipelines for platform and agent deployments

Agent & Workflow Engineering

Build, configure, and optimize AI agents and agentic workflows on the Cogentiq platform
Implement orchestration patterns using agentic frameworks (e.g., LangGraph, CrewAI)
Translate business problems into scalable, production-grade agentic solutions

Reliability, Observability & Troubleshooting

Ensure platform reliability, observability, security, and governance compliance
Troubleshoot integration, deployment, and runtime issues across distributed systems
Collaborate closely with product, platform, and customer teams to resolve production issues

Enablement & Adoption

Drive onboarding, enablement, and adoption of Cogentiq across internal and customer teams
Act as a technical partner to stakeholders, helping them leverage agentic AI effectively

Required Skills & Experience

Strong Python development skills with solid OOP and system design fundamentals
Experience building backend services using FastAPI or equivalent frameworks
Strong API design and integration experience
Hands-on experience with Docker and Kubernetes (K8s)
Experience deploying platforms using CI/CD pipelines
Deep understanding of enterprise connectors:
MCP-based connectors
APIs & SDK-based integrations
Storage systems and business applications
Experience working with or integrating via Model Context Protocol (MCP)
Strong debugging and troubleshooting skills across distributed systems
Ability to understand business use cases and map them to practical technical solutions
Familiarity with AI-assisted development tools (Cursor, Claude Code, Copilot, etc.)

Nice to Have

Exposure to LLMs, RAG, and model orchestration concepts
Experience with cloud platforms (AWS, Azure, or GCP)
Understanding of observability, monitoring, and evaluation frameworks
Prior experience working on enterprise platforms or developer platforms

Outcomes & Impact

Faster enterprise onboarding and platform integration
Scalable, production-ready AI agent deployments
Increased adoption and enterprise usage of Cogentiq
High reliability, security, and governance compliance in production systems

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

Not 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!

Stack

python
fastapi
docker
kubernetes
mcp
langgraph
crewai
aws

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