Forward Deployed Engineer, Google Cloud, AI Expert Job at Valtech (Montreal)

Job Description

We are seeking a Forward Deployed Engineer (FDE) with deep expertise in Google Cloud and applied AI to embed directly with our enterprise customers and turn frontier AI capabilities into production-grade systems. This role is for an engineer who thrives on ambiguity, codes alongside customer teams, and owns AI initiatives end-to-end — from technical discovery through architecture, build, deployment, and handoff.

Job Responsibility

Embed within customer engineering teams and lead technical discovery sessions with business stakeholders, engineering leadership, and security to translate ambiguous business problems into clear AI architectures and delivery plans
Architect, code, and ship production-grade agentic AI solutions on Google Cloud — including multi-agent systems, MCP servers, sub-agents, skills, connectors, agentic wrappers, and safety guardrails — that move customers beyond pilots into measurable business value
Design and implement Retrieval-Augmented Generation (RAG) pipelines and grounding architectures, including chunking strategy, vector databases, and embedding optimization to prevent hallucinations and ensure response quality
Build the “connective tissue” between Google’s AI products and customer infrastructure, including APIs, legacy data silos, identity, and security perimeters
Implement multi-agent patterns such as ReAct, self-reflection, and hierarchical delegation using frameworks like Google’s Agent Development Kit (ADK) or LangGraph
Build high-performance evaluation pipelines and observability frameworks for agentic systems, with attention to accuracy, safety, latency, cost-per-request, and tokens-per-second
Debug agent logic and optimize tool selection in live, high-traffic environments, including tracing conversation and request IDs across microservices to resolve production failures
Co-build with customer engineering teams and act as a hands-on advocate for AI-assisted development, introducing and operationalizing AI coding tools to accelerate delivery and elevate engineering practices
Drive a deliberate handoff to the customer’s team, ensuring long-term ownership, documentation, and end-user adoption after the engagement concludes
Develop and maintain technical documentation, architecture decision records, and evaluation results across all assigned engagements

Requirements

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience
5+ years of software development experience using Python, TypeScript, or comparable languages, with a track record of shipping production-grade code to external or internal customers
Hands-on experience architecting and deploying AI systems on Google Cloud Platform (GCP), including: Vertex AI — model deployment, fine-tuning workflows, evaluation, and platform-level observability
Gemini models — prompt engineering, structured outputs, function/tool calling, and multimodal use cases
BigQuery and Cloud Storage — as data and grounding sources for AI workloads
Cloud Run, Cloud Functions, and Pub/Sub — for deploying and orchestrating agentic services
Gemini Enterprise Agent Platform — designing, configuring, and deploying enterprise-grade agents, grounding on customer data sources, integrating tools and connectors
Demonstrated experience building agentic and AI-driven solutions in production, including: LLM application development — prompt engineering, agent development, and evaluation frameworks
RAG architectures — vector databases, chunking strategy, and retrieval evaluation
Data pipelines — structured and unstructured data ingestion to power enterprise-grade AI solutions
Experience deploying cloud resources via Terraform or similar infrastructure-as-code tools
Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI requirements and translate ambiguous business goals into technical roadmaps
Experience integrating AI systems with enterprise IT infrastructure, including authenticated APIs, legacy data systems, and corporate security perimeters
Ability to travel up to 50% of the time to customer sites
AI proficiency for productivity
Outstanding communication skills, including the ability to explain complex AI and architectural concepts to both deep-technical engineers and non-technical executives

Nice to have

Master’s degree or PhD in AI, Computer Science, Machine Learning, or a related technical field
Experience implementing multi-agent systems using frameworks such as Google’s Agent Development Kit (ADK), LangGraph, or CrewAI, and complex agent patterns including ReAct, self-reflection, and hierarchical delegation
Hands-on experience designing and deploying Model Context Protocol (MCP) servers, tool-calling protocols, and connector ecosystems for agentic systems
Knowledge of “LLM-native” operational metrics (tokens/sec, cost-per-request, time-to-first-token) and techniques for optimizing state management, granular tracing, and conversation-ID propagation across microservices
Track record of troubleshooting live, high-traffic production AI systems during critical windows
Experience architecting AI solutions within complex infrastructures, including data sovereignty, secure governance, and air-gapped or regulated environments
Experience designing user-facing interfaces for AI and agentic systems with attention to context engineering, transparency, and explainability
Experience driving organization-wide initiatives (e.g., migrations to new AI stacks, engineering-velocity programs) that deliver measurable improvements to engineering productivity and business outcomes
Experience as an advocate for AI-assisted software development, including introducing AI coding assistants to enterprise engineering teams and developing internal best practices for their use
Google Cloud certifications: Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Cloud Architect
Google Cloud Professional Data Engineer
Familiarity with full-stack application development and REST/GraphQL API design

What we offer

Comprehensive insurance plan (Gold, Silver, or Bronze) with employer contribution up to 80%
Dialogue via Sun Life virtual healthcare services
Employee and Family Assistance Program
Complete mental health support program
$500 Personal Spending Account
Retirement plan with Valtech matching 100% of RRSP contributions up to 4% via DPSP
Flexible vacation policy
Personal Technology Reimbursement $30/month
Winter holiday closure
Flexible scheduling

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Forward Deployed Engineer, Google Cloud, AI Expert

Job Description

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Requirements

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