Upwork

AI Productivity Solutions Engineer

Upwork

contract

Posted on:

Origin:  • 💃 Anywhere in Latin America

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Job Level

Mid-LevelSenior

Tech Stack

AWSAzureCloudETLGoogle Cloud PlatformJavaScriptNode.jsPython

About the role

  • Upwork ($UPWK) is the world’s work marketplace. This is an engagement through Upwork’s Hybrid Workforce Solutions (HWS) Team; HWS is a global group of professionals that support Upwork’s business. Design and develop AI-powered tools and applications to improve productivity across Upwork. Build and maintain scalable, secure, and reliable server-side services and APIs. Integrate AI technologies, LLMs, MCP, RAG, and other advanced architectures into workflows and business systems. Develop and maintain integrations with existing SaaS solutions via their APIs, leveraging integration platforms or custom connectors. Collaborate with stakeholders to identify pain points, map business processes, and design AI-driven solutions. Develop end-user applications that make AI capabilities intuitive and accessible to non-technical audiences. Create and manage ETL processes, pipelines, and data models for AI and analytics workloads. Prototype and experiment with emerging AI tools to evaluate potential business impact. Apply modern authentication and security practices, including OAuth 2.0, OpenID Connect, and SAML. Ensure operational excellence in the deployment, monitoring, and scaling of AI solutions.

Requirements

  • Proven track record building production-grade server-side applications (Node.js, Python, or similar). Deep understanding of AI concepts, including LLM APIs, prompt engineering, MCP, and related frameworks. Experience designing integrations between AI solutions and enterprise tools (e.g., Google Workspace, Jira, Slack, Notion) via APIs or middleware platforms. Familiarity with SaaS ecosystem APIs and integration solutions. Understanding of modern authentication and security protocols, including OAuth 2.0, OpenID Connect, and SAML. Solid grounding in cloud infrastructure (AWS, GCP, or Azure) and DevOps practices. Experience with ETL, data transformation, and working with large structured/unstructured datasets. Strong communication skills to translate technical concepts into business value. Ability to work autonomously on complex projects and deliver measurable outcomes.