Lead hands-on design, build, and production of LLM-powered applications and agent workflows. Own end-to-end delivery: backend APIs, integrations, orchestration, deployment, monitoring, and iteration. Translate stakeholder needs into practical, scalable architectures, embed AI into enterprise workflows, and ensure secure, observable, compliant AI operations while contributing shared libraries and engineering patterns.
We are looking for a Staff-level Forward Deployed AI Engineer to design, build, and deliver AI-powered applications that create measurable business impact.
This is a hands-on engineering role with strong design responsibility — you will spend most of your time writing code, integrating systems, and taking solutions to production, while also shaping practical, scalable designs that ensure what you build can operate reliably at enterprise scale.
You will work closely with business stakeholders to identify high-value opportunities, rapidly prototype solutions, and evolve them into well-architected, production-grade systems.
What You Will Be Responsible For:
- Design, develop, and deploy AI-powered applications and workflows
- Write production-quality code across:
- Backend services and APIs
- AI orchestration layers and agents
- Enterprise integrations
- Rapidly prototype solutions and iterate them into scalable production systems
- Own delivery end-to-end: build, test, deploy, monitor, and improve
- Translate use cases into clear, implementable system designs
- Make architecture decisions that balance:
- Speed of delivery
- Scalability and reliability
- Cost and operational efficiency
- Define patterns for:
- API-first integrations
- AI orchestration and workflows
- Reusable services and components
- Ensure systems are simple enough to build quickly, but structured enough to scale
- Embed LLM capabilities into products, internal tools, and business processes
- Build and maintain APIs and system integrations
- Implement agent workflows and orchestration logic that solve real operational problems
- Optimize systems for performance, resilience, and cost efficiency
- Work directly with stakeholders to understand problems and validate solutions
- Translate requirements into working software quickly (days/weeks, not months)
- Iterate based on feedback and usage to drive measurable impact
- Build and contribute to shared libraries, templates, and services
- Establish practical patterns based on real implementations
- Help evolve internal platforms through code and working solutions, not just design artifacts
- Implement secure and reliable AI solutions in practice, including:
- Prompt safety and validation
- Injection/misuse prevention
- Observability and traceability
- Align implementations with enterprise security, privacy, and compliance requirements
- Cloud & Platform: Microsoft ecosystem (Azure)
- AI Models: Claude and other enterprise-approved LLMs
- Architecture Style: API-first, event-driven, and modular services
- Core Focus:
- AI application engineering
- Orchestration and agent workflows
- Enterprise integrations
You will play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.
1. Build & Ship AI Applications (Primary Focus)
2. Design Practical, Scalable AI Systems
3. Integrate AI into Real Enterprise Workflows
4. Partner with Business & Deliver Outcomes
5. Contribute to Engineering Standards & Reuse
6. Build Within a Governed AI Environment
Technology Environment
What you bring:
- Proven ability to build and ship production systems at scale
- Strong experience in:
- Backend development and API design
- Cloud-native systems (Azure preferred)
- Integration-heavy, distributed applications
- Comfortable operating in a high-output, hands-on environment
- Ability to design clean, practical architectures that support real-world constraints
- Experience making trade-offs across:
- delivery speed vs scalability
- simplicity vs flexibility
- Can move fluidly between coding and design thinking
- Hands-on experience building LLM-powered applications in production
- Strong understanding of:
- Prompt design and evaluation
- Agent-based workflows and orchestration
- Integrating AI into production systems
- Ability to debug, tune, and improve AI behavior in code
- Bias toward shipping and learning from production usage
- Comfortable moving from idea → prototype → production
- Strong ownership: you build it, you run it
Hands-On Engineering Strength (Critical)
System Design & Architecture Judgment
AI / GenAI Development
Execution Mindset
EQ Bank | Equitable Bank Toronto, Ontario, CAN Office
30 St Clair Avenue West, Suite 700, Toronto, Ontario, Canada, M4V 3A1
Similar Jobs
Sales • Software
Manage and grow a team of forward-deployed engineers building and orchestrating agentic, multi-agent AI workflows. Serve as the technical liaison to customers and product/engineering, troubleshoot deployments and integrations, optimize performance in high-stakes domains like healthcare, and create tools, docs, and reference implementations to scale rollouts.
Cloud
As a Principal Forward Deployed Engineer at Okta, you lead strategic deployments, shape reference architecture, coach teams, and represent technical authority on agent identity to senior executives.
Top Skills:
AbacCedarOauth 2.0OidcOpaOpenfgaRebacRfc 8693SAMLScim
Cloud
The engineer will deploy Okta's agent security solutions at customer locations, collaborate with teams, and ensure agent identity and security protocols are met.
Top Skills:
AbacAgentforceBedrockCedarChatgptClaudeCrewaiLangchainMcp ServersMicrosoft CopilotOauth 2.0OidcOpaOpenai Agents SdkOpenfgaRebacRfc 8693 Token ExchangeSAMLScim
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.
