Forward Deployed AI Engineer at Banyan Software in Toronto, Ontario, Canada

Job description

• The Forward Deployed AI Engineer plays a critical role in how Banyan applies AI across our internal business functions — Operations, Finance, Human Resources, Legal, and beyond. You will understand how our teams work, reimagine the workflows behind them, and build the high-value AI tools that make our functions faster, sharper, and smarter: automating triage and reporting, forecasting demand and capacity, surfacing risk and cost insights, and streamlining the repetitive work behind each function. The common thread across every function is the same thing: get close to the work, find the problem worth solving, and build something that materially changes how the team operates.
• You will join a world-class operation sitting on a vast quantity of high-quality data waiting to be leveraged. Think of yourself as a builder and a translator, fluent in what modern AI can do and trusted to bridge business needs and technical capability. You will get close enough to the work to understand what teams are trying to achieve, define what good looks like, and determine how technology can get them there - sometimes by buying an existing solution, more often by building it yourself.

Responsibilities

• · Embed and own the process. Learn the systems, KPIs, and pain points well enough that the teams you support treat you as one of their own.
• · Find where AI can most change how work gets done. Identify high-value opportunities across functions, then sequence the work by impact, effort, and risk.
• · Turn ambiguous business problems into working solutions. Understand what stakeholders are trying to achieve, prototype quickly, and build successful solutions to scale.
• · Build AI-native tools. Prototype and ship applications using LLMs, retrieval, and agentic workflows, using AI-assisted development tools such as Claude Code as part of how you work
• · Make the build-versus-buy call. Bring a clear point of view on the trade-offs, with an expectation that many of our highest-value solutions will be built internally.
• · Make the ROI case and translate in both directions. Define what success looks like, then turn business problems into scoped technical requirements and technical decisions back into language the team can act on.
• · Drive adoption and set the patterns. Train teams, measure real impact after launch, and share what works across the wider Technology & Data Strategy team.

Requirements

• · 6 to 10 years of experience across software engineering, analytics, strategy, finance, or product, including at least 3 years hands-on in AI or building AI-enabled applications. Bachelor's degree in a quantitative, business, or technical field required; master's a plus
• · Demonstrated experience shipping production AI tools, including LLM applications, retrieval systems, or agentic workflows, from prototype to real users.
• · Hands-on experience building with automation/orchestration platforms such as n8n (or a comparable platform) and designing and shipping bespoke applications on AWS. Able to evaluate the trade-off between the two and choose deliberately.
• · Solid engineering practice: code in GitHub with reviewed pull requests, tests, and secrets handled properly, and infrastructure defined as code. Working knowledge of CI/CD, environment separation, staged rollout, monitoring, and rollback.
• · Strong SQL and solid data modelling instincts, command of Excel, and working knowledge of modern BI tools such as Looker, Power BI, or Tableau. Demonstrated ability to work with messy, real-world data.
• · Working command of modern AI technologies, including LLMs, retrieval, agentic workflows, model evaluation, data quality, and the practical limits of AI.
• · AI-native approach to development. Comfortable using AI-assisted development tools such as Claude Code as part of your day-to-day workflow to prototype, build, test, and iterate effectively.
• · Strong financial and commercial acumen, with the ability to build a credible business case and communicate it clearly to non-technical stakeholders.
• · Forward-deployed or production AI experience is a plus — time in a Forward Deployed Engineer, Solutions Engineer, or hands-on consulting role, or experience shipping LLM applications, retrieval systems, or agentic workflows in real business environments.

Skills

Required

• AI/LLM application development
• Retrieval systems
• Agentic workflows
• AWS
• GitHub with reviewed pull requests
• Testing
• Secrets management
• Infrastructure as code
• CI/CD
• Environment separation
• Staged rollout
• Monitoring

Preferred

• Forward Deployed Engineer experience
• Solutions Engineer experience
• Hands-on consulting experience

Benefits

• The expected base salary for this position is: CAD $145,000 – $170,000 excluding annual bonus and equity (when applicable). Salary is based on a number of factors including market conditions, location and may vary depending on job-related skills and experience.