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.
Requirements
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.
Benefits
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).
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