We are working with a US-based client in the veterinary technology and pet healthcare industry. The client provides digital solutions connecting veterinary practices, pet owners, pharmacy services, and business partners.
We are supporting the client’s AI transformation, with a focus on AI tooling, agentic workflows, and scalable approaches to AI product development with the tech stack based on Vertex AI and related Google Cloud services.
We are looking for an experienced, hands-on AI Engineer who can independently own the solution from discovery and architecture through implementation, deployment, and evaluation. The engineer will build a working MVP, compare the Google-based approach with the existing platform, present the results, and help train stakeholders on the selected AI tools and capabilities.
Review the existing MVP for AI/MCP solution implemented using Airia and define the scope and success criteria for the MVP using Google stack.
Partner with business and product stakeholders to define the use case, requirements, constraints, expected outcomes, and measurable success criteria.
Collaborate with engineering and security teams to establish the delivery plan, technical milestones, dependencies, and ownership, resolve blockers, and drive the MVP through implementation.
Design and personally implement an end-to-end solution using Vertex AI and Google Cloud.
Build AI agents, agentic workflows, tool integrations, and MCP-based connections.
Integrate the solution with internal data, APIs, and business systems.
Implement essential security, evaluation, observability, and cost controls.
Demonstrate the MVP and clearly communicate technical trade-offs to engineering and business stakeholders,
Train stakeholders on AI capabilities, tools, and responsible usage.
Support the development of an internal AI training and enablement program.
Document, demonstrate, and hand over the solution to the client’s engineering team.
8+ years of hands-on software, cloud, and solution-engineering experience.
Recent practical experience building and deploying AI and agentic solutions.
Strong Python skills and the ability to implement an end-to-end solution independently.
Hands-on experience with Vertex AI, Gemini, and Google Cloud.
Experience with agentic workflows and AI tooling such as Google ADK, LangGraph, LangChain, or similar frameworks.
Experience with MCP, function calling, and connecting AI agents to external tools and data.
Understanding of RAG, model evaluation, AI security, observability, and cost management.
Experience delivering an AI solution from discovery through a working MVP or production deployment.
Strong cross-functional collaboration and facilitation skills, including aligning engineering and business stakeholders, defining success criteria, and driving delivery milestones.
Excellent presentation and communication skills, including demonstrating technical solutions and creating clear training and enablement materials.
Strong English for direct collaboration, presentations, and training with client stakeholders.
Experience comparing AI platforms or build-versus-buy options.
TypeScript and enterprise integration experience.
