Senior Engineer, Applied AI

General Information:

Job Title: Senior Engineer, Applied AI

Location: Toronto, ON (Onsite/Hybrid)

Job Type: Full-Time

Hiring Timeline: Immediate

Reporting Line: Head of R&D

Existing Vacancy: Yes

Salary Range: 135K - 170K CAD per year (negotiable)

About Fulfillment IQ (FIQ):

Fulfillment IQ is a supply chain engineering and transformation company that helps brands, retailers, and 3PLs design, build, and scale high-performance logistics operations.

We work at the intersection of strategy, operations, and technology where we solve complex, real-world problems across warehouse design, automation, order management, transportation, and end-to-end supply chain execution.

Our teams combine deep domain expertise with strong technical capability, delivering outcomes through consulting, systems implementation, and proprietary platforms that accelerate time-to-value and reduce delivery risk.

If you enjoy working in complex environments, partnering closely with clients, and seeing your work make a tangible impact on how global commerce moves, this is the place where your skills and judgment truly come to life.

Role Overview:

This is a high-impact, senior engineering role , where engineers are expected to operate with significant ownership and minimal oversight. The role focuses on building production-ready AI systems in an environment where speed, correctness, and architectural decisions have long-term implications.

Ideal Candidate's Profile:

A seasoned AI engineer ( ninja-level ) with hands-on experience in developing and deploying real LLM systems, who excels in environments with significant ownership responsibilities and values impactful work more than structured, low-risk settings.

Individuals driven by ownership, autonomy, and the opportunity to build from the ground up (rather than being a small cog in a large organization) will thrive here.

Responsibilities & Expectations:

Key Responsibilities:

• Design and build production-grade LLM systems (RAG, agents, APIs)
• Architect systems that minimize rework in fast-evolving environments
• Own end-to-end delivery of critical AI features
• Define and implement evaluation frameworks
• Optimize systems for cost, latency, and reliability
• Collaborate across teams where needed
• Provide technical guidance where applicable (especially for less experienced engineers on adjacent teams)
  
  

Must-Haves (non-negotiables):

• Strong backend/software engineering foundation (Python, APIs, system design)
• Proven experience shipping LLM-powered features to production (non-negotiable)
• Deep expertise in:
• RAG systems (advanced retrieval + evaluation)
• LLM evaluation methodologies (golden sets, regression testing)
• Prompt engineering at API level
• Agent architectures (ReAct, tool calling, planning loops)
• Strong understanding of trade-offs (cost, latency, scalability)
• Ability to work independently in ambiguous, fast-moving environments
  
  

Nice-to-Have:

• Fine-tuning experience (LoRA, SFT, DPO)
• Inference stack experience (vLLM, TGI, llama.cpp)
• Observability tooling (Langfuse, LangSmith)
• Prior experience in early-stage or high-ownership teams
• Public work (GitHub, blogs, talks) demonstrating depth
  
  

Education:

• Bachelor's or master's degree in computer science or a related discipline
  
  

Technical Skills:

• Advanced Python and backend engineering
• LLM systems (RAG, agents, prompting, evaluation)
• API design and system architecture
• Docker, Git, CI/CD
• Understanding of inference systems and scaling
  
  

Soft Skills:

• High ownership and accountability
• Ability to operate in ambiguity ("build while flying")
• Strong decision-making and trade-off analysis
• Clear communication with cross-functional teams
  
  

What Success Looks Like in the First 90 Days:

By the end of Month 1:

• Deeply understand Crosstalk/Zync architecture and ongoing projects
• Contribute meaningfully to ongoing systems (not just onboarding tasks)
• Identify gaps or risks in current implementations
  
  

By the end of Month 2:

• Own and deliver a critical feature or system component end-to-end
• Improve an existing system (performance, evals, or architecture)
• Demonstrate strong independent execution
  
  

By the end of Month 3:

• Act as a trusted senior engineer on the team
• Drive architectural decisions or improvements
• Deliver measurable impact (system reliability, quality, or efficiency)
• Operate with minimal oversight in high-stakes projects
  
  

Why You'll Love Working Here:

At Fulfillment IQ, we don't just build supply chain solutions. We build careers, friendships, and unforgettable experiences.

We believe in giving our senior technical leaders real ownership, real influence, and the opportunity to shape platforms that power real-world logistics operations.

As an equal opportunity employer, we celebrate diversity and are committed to creating an inclusive environment for all team members.

Here's what makes working with us a rewarding experience:

Work That Matters

Build systems that directly impact global commerce and supply chain performance.

Career Growth That Matters

We invest in mentorship, leadership development, learning budgets, and long-term career growth.

Flexibility to Thrive

We support remote and hybrid work models by offering multiple office locations to help you perform at your best.

We Celebrate You

From team wins to work anniversaries, we recognize impact, celebrate milestones and reward performance.

A Collaborative Culture

Work alongside talented engineers, product leaders, and award-winning domain experts who value ownership, transparency, and high standards.

Perks you'll appreciate:

• Employee Health: Comprehensive health and dental coverage for you and your family
• Time Off: Competitive paid time off and flexible leave policies
• Retirement: Retirement savings programs and employer contributions
• Professional Growth: Dedicated learning and development budget
• Flexible Work: Remote and hybrid work options
• Perks: Equipment allowances, internet reimbursements, business travel coverage, and employee stock options (ESOP), where applicable.
• Community Engagement: Team events, meetups, and company offsites
  
  

Use of Artificial Intelligence in Hiring:

FIQ uses artificial intelligence to assist in the screening, assessment, and shortlisting of applications for this position, including features within our applicant tracking system. AI supports human reviewers and does not make hiring decisions on its own. Final hiring decisions are made by FIQ personnel. If you have questions about how AI is used in this process, contact [email protected].

Accommodations:

FIQ is committed to an inclusive and accessible recruitment process. Consistent with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code, accommodations are available on request at any stage of recruitment and assessment. Contact [email protected] and we will work with you to meet your needs.

Candidate Privacy:

Your personal information is collected and used for recruitment purposes in accordance with FIQ's Candidate Privacy Notice, available here, and in accordance with applicable Canadian privacy law (PIPEDA). This includes the use of AI-assisted screening described above and cross-border storage or processing that may occur in the United States. By applying, you acknowledge this notice. Questions: [email protected].

Equal Opportunity:

Fulfillment IQ is a people-first company built on trust, collaboration, and ownership. We are proud to be an equal opportunity employer and are committed to building a diverse, inclusive, and high-performing workplace. We consider all qualified applicants without regard to any ground protected under the Ontario Human Rights Code, including race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, or disability.

Learn More About Us:

Website: fulfillmentiq.com

LinkedIn: Fulfillment IQ

Spotify: eCom Logistics Podcast Spotify

YouTube: eCom Logistics Podcast YouTube

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