About the company
Our client is a Google Cloud partner helping mid-to-large enterprises move from experimental AI to production-grade enterprise AI. We connect ERP systems, legacy platforms, internal databases and sources like SAP and Salesforce into Gemini Enterprise and GCP-native AI workflows, then layer agentic automation and governance on top.
We are a small, early-stage team based in Toronto, with an engineering team in India handling delivery. We are now building out our AI practice in Europe.
The role
You will be the technical lead for the company's AI work with European clients. This is a forward-deployed, high-ownership role: you run technical discovery with enterprise stakeholders, design the solution, and hand it off to our engineering team in India to deliver.
The role leans toward architecture, solutioning and client leadership, with hands-on engineering where it moves the work forward. You will also help shape how the practice grows in the region.
What you'll do
- Lead technical discovery with enterprise clients, including CIO-level stakeholders, and translate business problems into AI solutions.
- Design solution architecture for agentic AI on Google Cloud, integrating ERP, legacy and enterprise data sources.
- Choose the right frameworks and approach for each engagement.
- Write clear handoff specs and coordinate delivery with the India engineering team, owning quality from design to production.
- Build prototypes and contribute hands-on code where it speeds up delivery.
- Help build the company's European AI practice: repeatable patterns, client relationships and how we work.
What we're looking for
Technical skills
- Strong Python development skills, with practical experience building production services, automation or data pipelines.
- Hands-on experience with generative AI and modern foundation models, such as Gemini, OpenAI, Anthropic or open-source models.
- Working knowledge of LLM application patterns: RAG, embeddings, tool and function calling, structured outputs and agentic workflows.
- Understanding of the Model Context Protocol (MCP), modern agent integration patterns and agent-to-agent interoperability.
- Experience with APIs, Git, Docker, CI/CD, cloud-native development and production troubleshooting.
- Practical GCP experience across areas such as Vertex AI, Cloud Run, GKE, BigQuery, Cloud Storage, Cloud SQL, Pub/Sub, Dataflow, Artifact Registry, IAM, Secret Manager and Cloud Monitoring and Logging.
- Awareness of AI security, responsible AI, data privacy, access control, evaluation, observability, reliability and cost management.
- The judgment to evaluate new models, frameworks, protocols and AI tooling against measurable production requirements, not demos alone.
Client and delivery experience
- 4 to 8 years of experience in software engineering, solutions architecture or technical consulting.
- Experience integrating legacy systems and enterprise data, such as ERP, SAP, Salesforce or internal databases.
- Strong client-facing communication and confidence working with senior enterprise stakeholders.
- Experience coordinating offshore or distributed delivery teams.
- Fluent professional English.
- You thrive on a small, fast-moving team with real ownership.
Nice to have
- Background at a consultancy, systems integrator or Google Cloud partner.
- Experience with Dialogflow, Agent Builder or Vertex AI Search.
- Experience with agent frameworks such as LangGraph, LangChain or Google ADK.
- Google Cloud certifications.
- A track record of bridging technical and business teams.
Why join
- A founding role: you help build the European AI practice from the ground up.
- Production agentic AI for real enterprise clients, not endless proofs of concept.
- A mix of client leadership, architecture and hands-on work, backed by a dedicated engineering team.
- Fully remote, with the ownership and pace of an early-stage company.
- Competitive compensation and benefits.
We appreciate every application. Due to the high volume we receive, only candidates selected for an interview will be contacted.