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 straightforward 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

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📌 Forward Deployed AI Engineer (Ontario)
🏢 EQ Bank | Canada's Challenger Bank
📍 Ontario