Responsibilities
- Evaluate and prototype GCP tools like Agentspace ADK to identify the best fit for our needs
- Build and maintain internal AI tools and workflows, acting as the go-to contact for support requests
- Implement and manage an internal AI agent/workflow manager (e.g., Agentspace or similar), including access controls and change management
- Manage projects related to data sources and AI-powered tools, focusing first on internal productivity gains, with learnings later applied to customer-facing tools
- Lead technical discovery sessions with different departments to uncover high-impact AI use cases
- Translate complex technical strategies into plain language for non-technical stakeholders
- Partner with IT, Engineering, People, and leadership teams to roll out solutions that scale
Requirements
- Experience working directly with AI or LLM technologies and guiding others in their adoption
- Background in computer science, software engineering, or related technical field
- Experience deploying and maintaining cloud-based applications or automations, focusing on security, access, and collaboration
- Proven ability to lead projects end-to-end and document requirements, test plans, and deployments clearly
- Familiarity with APIs, connectors, integration strategies, preferably with Google Cloud Platform or AWS
- Knowledge of identity and access management protocols (OAuth, OIDC, SAML) and system security
- Excellent communication skills bridging technical and non-technical teams
Nice to Have
- Experience with Retrieval-Augmented Generation (RAG) pipelines
- Strong Python and SQL programming skills
- Experience with containerized workloads, CI/CD pipelines, and monitoring tools
- Experience managing Model Context Protocol (MCP) servers
