We are looking for a Staff Engineer, AI & Engineering who can bridge deep software engineering expertise with practical AI implementation. This role is ideal for a senior technical leader who has built scalable software systems and has experience leveraging AI technologies to solve complex business problems.

You will partner closely with Engineering, Product, Data, and Technology leaders to design and deliver contemporary, resilient, and intelligent solutions. While experience with AI and machine learning technologies is important, this role is fundamentally an engineering leadership position focused on architecture, platform development, system design, and software delivery excellence.

This is a hands-on role requiring robust technical depth, architectural thinking and the ability to influence engineering direction across multiple teams.

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) 8+ years of software engineering experience building and delivering scalable, production-grade applications and platforms. Demonstrated success leading complex technical initiatives from design through deployment and ongoing operations. Strong engineering fundamentals with the ability to influence technical direction across teams and organizations.

System Design & Architecture Judgment Deep expertise in designing scalable, resilient, and maintainable software architectures.

Experience making trade-offs across:

delivery speed vs scalability

simplicity vs flexibility

Can move fluidly between coding and design thinking

AI / GenAI Development 3+ years of hands‑on experience building and deploying AI/Generative AI solutions in production environments.

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

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📌 Staff Engineer (AI & Engineering) (Winnipeg)
🏢 Socket.dev
📍 Winnipeg