> Markdown version of [/jobs/ext/3928999-lead-enterprise-solution-analyst](https://www.wearedevelopers.com/jobs/ext/3928999-lead-enterprise-solution-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Enterprise Solution Analyst - **Company:** Paramount Global - **Location:** Los Angeles, CA, United States - **Experience:** Expert - **Salary:** $124,000 - $186,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Engineering, JSON, Python (Programming Language), Automation of Marketing, Robotic Automation Software, Systems Integration, Management of Software Versions, Web Applications, YAML, Data Logging, Enterprise Software Applications, Multi-Agent Systems, IT Architecture, Generative AI, Agentic-AI, Git, Fastapi, Containerization, AI Platforms, Uipath, Information Technology, Deployment Automation, Machine Learning Operations, Artificial Intelligence Governance, Api Design, Software Version Control, Automation Anywhere, Docker - **Published:** October 26, 2026 - **Apply:** https://www.beyondlosangeles.com/job.asp?id=3467429339&tx=KK8383FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 8+ years of experience in infrastructure architecture, AI platforms, or enterprise systems integration, including hands-on development using Python and API-based services. * Strong expertise in Azure cloud services with proven experience building and operating CI/CD pipelines, Git-based version control, and cloud-native deployments (App Services, Functions, containers). * Demonstrated technical lead experience, including leading or coordinating offshore or globally distributed engineering teams, establishing engineering standards, and delivering enterprise scale AI, automation, or orchestration solutions., * Experience designing or implementing AI orchestration frameworks, including multi-agent systems, workflow coordination, or retrieval-augmented generation (RAG) patterns. * Familiarity with enterprise automation platforms such as Automation Anywhere, UiPath, or equivalent RPA tools. * Experience building and deploying API-driven services using frameworks such as FastAPI, with configuration-driven logic using YAML / JSON. * Working knowledge of containerization (Docker) and cloud-native deployment strategies across multiple environments. * Experience implementing observability, logging, telemetry, and monitoring for distributed AI and automation platforms. * Solid understanding of MLOps practices, including model lifecycle management, versioning, and governance. * Proven ability to collaborate with product, data, security, and platform teams to deliver reusable, enterprise-scale AI capabilities. * Excellent technical documentation and architectural communication skills for executive and engineering audiences. * Bachelors or Masters degree in Computer Science, Engineering, or a related discipline, or equivalent experience ## Description Paramount Tech is hiring a Lead Enterprise Solution Analyst to architect and oversee the enterprise AI orchestration framework, integrating automation, RPA, and multi-agent systems across the companys technology ecosystem. This role blends strategic architecture, infrastructure leadership, and hands-on engineering to ensure secure, scalable, and high-performance AI deployments., * Designing and implementing the AI orchestration layer that connects automation engines, AI agents, and enterprise applications. * Building infrastructure pipelines to support AI/ML deployment and Azure web application services across cloud environments. * Defining and enforcing standards for MLOps, APIs, observability, and compliance to support enterprise-scale operations. * Partnering with product, data, and engineering teams to translate strategic business needs into reusable AI platform components. * Ensuring adherence to internal AI guardrails, SLAs, and security/compliance standards.