Sr. GenAI Tooling Engineer
Futran Tech Solutions Pvt. Ltd.
Senior GenAI Tooling EngineerSeeking a Senior GenAI Tooling Engineer with expertise in GenAI, LLMs, OpenAI, Azure AI, Agentic AI, RAG Pipelines, Python, Amplitude, and Jellyfish to drive enterprise AI tooling strategy, governance, implementation, platform adoption, and engineering productivity across a regulated environment.Roles and Responsibilities:AI Tool Strategy & Portfolio EvolutionPlatform Implementation & IntegrationPlatform Adoption & Engineering EnablementPlatform Success & OperationsEngineering Analytics & InsightsPlatform Optimization & Continuous ImprovementBusiness PartnershipDuration: Contract role with CitiusTechEducational Qualifications: Engineering Degree – BE/ME/BTech/MTech/BSc/MSc. Technical certification in multiple technologies is desirable.Skills:Experience in implementing, integrating, administering, or supporting enterprise software platforms.Strong experience implementing and supporting engineering productivity platforms such as Jellyfish, Amplitude, or comparable enterprise tools.Experience integrating enterprise platforms using APIs, webhooks, SSO, RBAC, cloud services, and automation.Experience onboarding engineering teams and applications to enterprise platforms.Experience building engineering dashboards, executive scorecards, operational KPIs, and adoption analytics.Strong scripting and automation skills (Python, PowerShell, APIs, automation workflows).Excellent communication, consulting, troubleshooting, stakeholder management, and customer success skills.Technical Skills & Technologies:Engineering Productivity Platforms: Jellyfish, Amplitude, Azure DevOps, GitHub, JiraAI-DLC, AI-QE & AI AppOps: LangSmith, Promptfoo, LangFuse, Arize, Phoenix, AI observability and evaluation platformsIntegration & Automation: REST APIs, Webhooks, Python, PowerShell, JSON, enterprise integrationsCloud & Identity: Microsoft Azure, Azure OpenAI, SSO, RBAC, identity integrationEngineering Analytics: Power BI or similar visualization platforms, engineering scorecards, KPIs, operational dashboards, adoption analyticsEngineering Practices: SDLC, Agile, DevSecOps, release management, platform operations, continuous improvementOrganizational Boundaries:Owns: AI Engineering productivity platforms, AI-DLC, AI-QE, AI AppOps, AI Observability, and AI Governance tools, Platform implementation, integration, onboarding, adoption, operations, optimization, and engineering analyticsPartners With: AI Infrastructure & Cloud teams, Enterprise Data & Analytics Platform teams, Enterprise Architecture, Security, Product, and Engineering organizationsSuccess Measures:Rapid onboarding of engineering teams and applications.High platform adoption, customer satisfaction, and feature utilization.Reliable platform operations, availability, and operational maturity.Actionable engineering dashboards and executive insights.Optimized licensing, integrations, platform performance, and engineering productivity.Continuous evolution of the AI engineering tooling ecosystem.
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