Forward Deployed Engineer

Forma.ai•Toronto, ON

About The Position

Forma.ai is hiring a Forward Deployed Engineer to work directly with our Revenue Optimization team and customers to build data-driven solutions for territory design, quota setting, market potential analysis, and seller performance. This role sits at the intersection of software engineering, applied data science, and customer delivery. You will embed closely with business and customer-facing teams, quickly understand each customer’s data and objectives, and turn ambiguous problems into working solutions. We are looking for someone highly driven, resourceful, and energized by solving difficult customer problems. You will be expected to take ownership, move with urgency, and persist through messy data, unclear requirements, and changing constraints to deliver meaningful outcomes. Early solutions may be customer-specific, including Python models, simulations, data workflows, reports, and rep-level recommendations. A key part of the role is identifying repeatable patterns and turning successful implementations into reusable tools, libraries, and workflows that can support future customers. This is not a traditional product engineering role. It is designed for someone who enjoys working close to customers, rolling up their sleeves, and owning problems from initial discovery through deployment and adoption.

Requirements

Strong professional experience using Python for data analysis, automation, applied data science, or backend development.
Strong SQL skills and experience working with complex, incomplete, or unfamiliar customer datasets.
Experience with Python libraries such as pandas, NumPy, SciPy, statsmodels, or scikit-learn.
A strong sense of ownership and the determination to work through difficult problems until they are resolved.
A bias toward action and the ability to deliver useful results without waiting for perfectly defined requirements.
Genuine enthusiasm for understanding customers’ businesses and solving problems that materially affect their outcomes.
Strong software engineering fundamentals, including modular design, testing, version control, code review, and documentation.
Experience deploying analytical workflows, internal tools, data pipelines, or customer-specific applications.
Strong communication skills and the ability to work directly with customers, executives, analysts, and engineers.
Comfort balancing rapid delivery with maintainability, security, and long-term reuse.
The resilience and organization required to manage multiple customer-facing workstreams with limited oversight.

Nice To Haves

Experience in sales planning, revenue operations, incentive compensation, territory design, or quota setting.
Experience with simulation, optimization, forecasting, geospatial analysis, or account scoring.
Experience in forward deployed engineering, solutions engineering, consulting, or professional services.
Familiarity with cloud data platforms, workflow orchestration, and SOC 2-controlled environments.

Responsibilities

Work directly with Revenue Optimization leaders, analysts, and customers to understand their objectives, data, and operational constraints.
Build and deploy Python-based models, simulations, reports, and recommendations for territory planning, quota design, market potential, and seller performance.
Own customer problems from discovery and prototyping through validation, deployment, documentation, and adoption.
Move quickly through ambiguity, investigate issues deeply, and do what is needed to deliver a reliable customer outcome.
Turn successful customer-specific implementations into reusable components, workflows, and internal tools.
Ensure all solutions use approved infrastructure and meet security, auditability, and customer-data requirements.