Posted last month
Forward Deployed AI Engineer
@ Urban Ridge Supplies
Toronto, Ontario
Overview
Urban Ridge Supplies is hiring a Staff-level Forward Deployed AI Engineer, a full-time hands-on role to design, build, and deliver AI-powered applications with measurable business impact. The work involves writing production code, integrating enterprise systems, and taking solutions from prototype to production on Azure.
Responsibilities:
- Build and ship AI-powered applications and workflows
- Design scalable, API-first AI system architectures
- Integrate LLM capabilities into enterprise workflows
- Partner with stakeholders to deliver measurable outcomes
- Build shared libraries and reusable AI services
Requirements summary:
- Proven experience building and shipping production systems at scale
- Strong backend development and API design skills
- Cloud-native experience, Azure preferred
- Hands-on experience with LLM-powered applications in production
- Understanding of prompt design, evaluation, and agent workflows
- Strong system design judgment and ownership mindset
Tools & skills
Source and dates
Employer career site / ATS feed · teamtailor
- Employer posting date
- 2026-09-24
- First seen by our source
- 2026-10-11
- Source record updated
- 2026-10-30
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Urban Ridge Supplies
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Supplying high-quality pipes for residential, commercial, and industrial needs.
Full company description
Supplying high-quality pipes for residential, commercial, and industrial needs across Karachi. Fast delivery. Trusted quality.
- LinkedIn followers
- 14,005
- Reported office locations
- Sheikh Mohammed bin Rashid Boulevard 1, Zabeel, Dubai, AE
- Other recorded names
- Urban Ridge Supplies
- Profile identifies a recruitment agency
- No
Supplying high-quality pipes for residential, commercial, and industrial needs across Karachi. Fast delivery. Trusted quality.
| Field | Value |
|---|---|
| Industry | Wholesale Building Materials |
| Company size | 2-10 employees |
| Headquarters | Zabeel, Dubai |
| Organization type | Privately Held |
| Open jobs on Jobsy | 124 |
| View page |
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.
- 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
- 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
- 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
- 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
- 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
- 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
- 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
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
- 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
Job Id: /4gL9VqJCPc0V6iwu7FhrnEzu56cMKnqWui3TkMSuk9tUwrTyo6j6EA0yjmvPFNezUx7bxMPv606Kbr68xAUoa8pBgdmwls5Hw==
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