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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 CogentiqAbout Cogentiq (Fractals Agentic AI Platform): Cogentiq is Fractals secure, scalable, enterprise agentic AI platform that enables teams to build, test, deploy, monitor agents and multiagent workflows with strong observability, evaluation, guardrails and RBAC across any cloud or LLM framework. It includes a no/lowcode development console, Agent & MCP Gateways, and an enterprise marketplace for reusable agents, tools, connections and guardrails. Role SummaryAs a Senior Platform Engineer Agentic AI, you will play a critical role in integrating, deploying, and scaling Cogentiq, Fractals enterprise-grade agentic AI platform, across complex customer environments. You will enable productionready 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 ResponsibilitiesPlatform Integration & DeploymentIntegrate 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 SDKsDeploy, configure, and operate Cogentiq across Core, Runtime (Kubernetes), and Governance layersSet up and maintain CI/CD pipelines for platform and agent deploymentsAgent & Workflow EngineeringBuild, configure, and optimize AI agents and agentic workflows on the Cogentiq platformImplement orchestration patterns using agentic frameworks (e.g., LangGraph, CrewAI)Translate business problems into scalable, production-grade agentic solutionsReliability, Observability & TroubleshootingEnsure platform reliability, observability, security, and governance complianceTroubleshoot integration, deployment, and runtime issues across distributed systemsCollaborate closely with product, platform, and customer teams to resolve production issuesEnablement & AdoptionDrive onboarding, enablement, and adoption of Cogentiq across internal and customer teamsAct as a technical partner to stakeholders, helping them leverage agentic AI effectivelyRequired Skills & ExperienceStrong Python development skills with solid OOP and system design fundamentalsExperience building backend services using FastAPI or equivalent frameworksStrong API design and integration experienceHands-on experience with Docker and Kubernetes (K8s)Experience deploying platforms using CI/CD pipelinesDeep understanding of enterprise connectors:MCP-based connectorsAPIs & SDK-based integrationsStorage systems and business applicationsExperience working with or integrating via Model Context Protocol (MCP)Strong debugging and troubleshooting skills across distributed systemsAbility to understand business use cases and map them to practical technical solutionsFamiliarity with AI-assisted development tools (Cursor, Claude Code, Copilot, etc.)Nice to HaveExposure to LLMs, RAG, and model orchestration conceptsExperience with cloud platforms (AWS, Azure, or GCP)Understanding of observability, monitoring, and evaluation frameworksPrior experience working on enterprise platforms or developer platformsOutcomes & ImpactFaster enterprise onboarding and platform integrationScalable, production-ready AI agent deploymentsIncreased adoption and enterprise usage of CogentiqHigh reliability, security, and governance compliance in production systemsIf 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! .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.