Forward Deployed Ai Engineer

Why Keyrus, Why Now!Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.
For more than 30 years, we have helped organizations build the data foundations that power intelligent systems. Today, we go further by designing and operationalizing intelligence that delivers measurable business value.
Building AI capabilities is only part of the challenge. Real transformation happens when those capabilities work within existing business systems, data environments, workflows, and processes.
At Keyrus, you'll work closely with clients to turn AI opportunities into production-ready solutions, connecting engineering expertise with real business needs.
Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.
What You'll ArchitectAs a Forward Deployed AI Engineer, you'll work directly with clients to take AI solutions from technical discovery through implementation, deployment, and adoption.
You'll combine hands-on software engineering, enterprise integrations, cloud technologies, and AI capabilities to deliver solutions that work in real client environments.
Your focus goes beyond writing code. You'll understand client challenges, define implementation plans, coordinate engineering teams, resolve integration issues, and deliver measurable results.
Your Responsibilities
Lead technical discovery with clients to understand their systems, data, workflows, security requirements, and technical challenges.
Translate business needs and approved architectures into practical implementation plans and deployment priorities.
Develop and integrate production-ready solutions using APIs, enterprise applications, cloud services, data platforms, and AI technologies.
Collaborate with AI Engineers, Software Engineers, Data Engineers, and Architects to coordinate implementation and resolve technical challenges.
Own technical deployment and rollout within the agreed scope, ensuring solutions operate reliably in client environments.
Support client teams during implementation, resolve technical issues, and enable successful adoption.
Monitor production performance, costs, and business outcomes while documenting solutions and reusable engineering practices.
Who You AreYou are a hands-on engineer who enjoys working directly with clients and solving complex technical challenges. You develop production-quality code, understand how systems connect, and adapt solutions to real-world constraints. You are comfortable with incomplete requirements, collaborating with specialists, and taking ownership of technical delivery. You combine technical expertise with strong communication, problem-solving, and client relationship skills.
ExperienceWhat you bring
Strong hands-on experience developing, integrating, and deploying production software, AI, data, or cloud solutions.
Experience writing, debugging, and maintaining production-quality code.
Experience integrating enterprise applications, APIs, data sources, authentication systems, and cloud services.
Ability to translate technical requirements into implementation plans and production deployments.
Experience working directly with clients or business stakeholders while maintaining technical ownership.
Strong communication skills to explain technical decisions, risks, and implementation challenges to different audiences.
Technical Skills
Strong programming skills in at least one language, such as Python, TypeScript/JavaScript, Java, or C#/.NET.
Experience with REST APIs, webhooks, enterprise integrations, and backend services.
Hands-on experience with at least one major cloud ecosystem, such as AWS, Azure, or GCP.
Knowledge of Git, testing, CI/CD, containers, and production monitoring.
Familiarity with AI/GenAI technologies, including LLM APIs, RAG, AI agents, and AI-enabled workflows.
Understanding of application security, authentication, identity management, and production deployment.
Nice to have
Experience building GenAI applications, RAG systems, or agentic workflows.
Familiarity with LangGraph, MCP, OpenAI, Anthropic, or similar technologies.
Background in backend, full-stack, data, or cloud/platform engineering.
Experience with complex enterprise or regulated environments.
Consulting or professional services experience across multiple clients.
Experience in Forward Deployed Engineering, Customer Engineering, or client-embedded technical roles.
What Makes You Successful
You turn complex challenges into practical solutions.
You take ownership of technical delivery and integration.
You communicate clearly and collaborate effectively with clients and teams.
You deliver reliable solutions that create measurable business value.
Role details
Location: Toronto / Montreal
Contract: Full-time
Work model: Hybrid
Level: Experienced / Senior
Rewards – What We Offer At Keyrus
International and multicultural projects
Opportunities to work with leading technologies in Data, Cloud, and AI ecosystems
Access to training programs and continuous professional development
Professional growth opportunities and internal mobility
A culture built on collaboration, innovation, and continuous learning
The expected base compensation for this position ranges from $90,000 to $120,000 CAD, depending on experience, skills, location, and internal equity. This salary range is provided as a guideline and may be adjusted for the selected candidate.
About KeyrusAt Keyrus, we help organizations move from experimental to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution.
As Architects of Intelligence, we design the Operating System of the intelligent enterprise, embedding intelligence into business processes so that it creates sustainable, measurable value.
Powered by our proprietary Human Orchestrated Model™ (HOM), we architect reliable:
Intelligence Foundations
Human in Command governance
Performance Steering
With over 30 years of expertise and 3,000 experts across 30 countries, we build adaptive, resilient intelligent environments where technology amplifies human capability and performance compounds over time.
AI does not transform businesses. Architected intelligence does.
For more information:
#J-18808-Ljbffr