About the role

Solutions Engineer addressing complex data challenges and enhancing customer growth through technical solutions at Fiscal.ai, a fintech startup.

Responsibilities

Technical Discovery: Partner with Account Executives to deeply understand a prospect’s technical stack, data requirements, and workflow pain points.
Solution Design: Architect bespoke solutions using the Fiscal.ai API and Terminal to demonstrate how our data can be integrated into their existing proprietary models or platforms.
Implementation Oversight: Lead the technical onboarding and implementation for new accounts, serving as the primary point of contact to ensure a smooth transition from "prospect" to "active user."
Strategic Consulting: Act as a long-term consultant for our key accounts, regularly reviewing their data usage to identify new opportunities, untapped use cases, and product expansions.
Post-Sales Technical Support: Provide high-level technical support for existing customers, troubleshooting integration issues and ensuring our API remains a mission-critical part of their stack.
Bridge to Product: Act as the "voice of the customer" for our engineering team, funneling market feedback into the product roadmap to ensure we stay ahead of the curve in financial AI.

Experience: 3+ years in a Solutions Engineering, Sales Support (Sales Engineer), or Technical Consulting role, ideally within Fintech, Capital Markets, or Enterprise SaaS.
Technical Proficiency: Strong ability to write and troubleshoot code (Python or JavaScript preferred) and a deep understanding of REST APIs and data structures.
Cloud Infrastructure: Hands-on experience with at least one major cloud provider (AWS preferred; GCP or Azure acceptable). Must be comfortable troubleshooting cloud-native environments, including networking issues such as VPC configuration, DNS resolution, firewall/security group rules, and API connectivity, to support customers running Fiscal.ai integrations in their own infrastructure.
Financial Literacy: You don't need to be a hedge fund manager, but you must understand how capital markets work and how financial data is consumed by institutions.
Consultative Mindset: Proven ability to advise clients on technical strategy and "see around corners" to identify new business opportunities within existing accounts.
Communication: The ability to explain "the how" to a developer and "the why" to a Managing Director in the same meeting.
Nice to Haves: Direct experience working with Large Language Models (LLMs) or RAG (Retrieval-Augmented Generation) architectures. Experience in a Technical Customer Success or Post-Sales Engineering role at a high-growth startup.

Base Salary: $110,000 – $140,000 CAD
Variable/Bonus: $30,000 – $40,000 CAD (Linked to sales targets and successful implementation milestones)
Equity: Meaningful stock options in a high-growth VC-backed startup.
Location: Hybrid 3 days in office (Toronto, Canada).