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EQ Bank
Forward Deployed AI EngineerEQ Bank • Toronto, Ontario, Canada
Forward Deployed AI Engineer

Forward Deployed AI Engineer

EQ Bank • Toronto, Ontario, Canada
26 days ago
Job type
  • Full-time
Job description
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:

You will play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.

1. Build & Ship AI Applications (Primary Focus)

  • 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

2. Design Practical Scalable AI Systems

  • 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

3. Integrate AI into Real Enterprise Workflows

  • 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

4. Partner with Business & Deliver Outcomes

  • 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

5. Contribute to Engineering Standards & Reuse

  • 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

6. Build Within a Governed AI Environment

  • 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

Technology Environment

  • 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

What you bring:

Hands-On Engineering Strength (Critical)

  • 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

System Design & Architecture Judgment

  • 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

AI / GenAI Development

  • 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

Execution Mindset

  • Bias toward shipping and learning from production usage
  • Comfortable moving from idea prototype production
  • Strong ownership: you build it you run it
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.

Required Experience:

IC


Employment Type : Full-Time
Experience: years
Vacancy: 1
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Forward Deployed AI Engineer • Toronto, Ontario, Canada

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