ref. no.
1001228
type
Remote
location
Toronto, ON
salary
$250000per
status
Permanent
Position: Senior AI Systems Engineer (Automation / Agents /Data Infrastructure)
Location: Fully Remote (U.S./Canada)
Salary: $250K+ base + equity
We’re partnered with a fast-growing, product-driven technology company operating within the sports and real-time data space. The team is building a platform that sits at the intersection of live data, analytics, and consumer-facing applications — helping users make faster, smarter decisions in highly dynamic environments.
Their product processes large volumes of real-time data across hundreds of external sources, and they are continuing to scale both their infrastructure and engineering team as adoption grows. This is a unique opportunity to join a small, high-impact team where engineers have direct ownership over systems, architecture, and product direction.
The Role:
We’re looking for an AI-native Engineer who is passionate about building systems that automate engineering workflows and significantly improve developer productivity. This role is focused on backend systems, data pipelines, and internal tooling rather than traditional feature development.
What You’ll Be Building:
- AI-driven workflows that generate, validate, and optimize code, scripts, and integrations
- Systems that automatically create and maintain real-time data pipelines across external data sources
- Internal developer tools that automate debugging, testing, and deployment processes
- High-scale ingestion pipelines processing large volumes of live data
- Monitoring systems that detect failures and proactively suggest fixes
What We’re Looking For:
- Experience building AI workflows, agents, or developer automation tools
- Strong background in distributed systems, backend infrastructure, or data pipelines
- Experience designing systems that run large volumes of automated jobs or integrations
- Exposure to LLM orchestration, AI tooling, or experimentation in this space
- A builder mindset — someone who has created systems, tools, or meaningful side projects
Ideal Profile:
- Enjoy building systems that eliminate repetitive engineering work
- Prefer infrastructure, tooling, and automation over traditional product features
- Move quickly, prototype often, and iterate based on real feedback
- Have hands-on experience with automation tools, scrapers, AI systems, or internal platforms
- Comfortable working in a fast-paced, early-stage environment with high ownership Tech StackGo, Python, TypeScript, Postgres, ClickHouse, AWS, and modern AI/LLM tooling
Why This Opportunity:
- High ownership — make real architectural decisions
- Work on systems that directly impact product performance and user outcomes
- Join a small, highly technical team solving complex real-time data problems
- Strong engineering culture focused on speed, quality, and impact
- Competitive compensation and meaningful equity
Interview Process:
- Intro call with the team
- Take-home challenge (practical, under 2 hours)
- Systems design discussion
- Final conversation with leadership
If you’re interested in building AI-driven systems in a real-time, high-scale sports data environment, this is a great opportunity to explore.
Please send your resume in Word format to Ian Ascuasiati at ian.ascuasiati@quantum-qtr.com.
REFER A NEW HIRE AND EARN A CASH BONUS! For details, click here.
Location: Fully Remote (U.S./Canada)
Salary: $250K+ base + equity
We’re partnered with a fast-growing, product-driven technology company operating within the sports and real-time data space. The team is building a platform that sits at the intersection of live data, analytics, and consumer-facing applications — helping users make faster, smarter decisions in highly dynamic environments.
Their product processes large volumes of real-time data across hundreds of external sources, and they are continuing to scale both their infrastructure and engineering team as adoption grows. This is a unique opportunity to join a small, high-impact team where engineers have direct ownership over systems, architecture, and product direction.
The Role:
We’re looking for an AI-native Engineer who is passionate about building systems that automate engineering workflows and significantly improve developer productivity. This role is focused on backend systems, data pipelines, and internal tooling rather than traditional feature development.
What You’ll Be Building:
- AI-driven workflows that generate, validate, and optimize code, scripts, and integrations
- Systems that automatically create and maintain real-time data pipelines across external data sources
- Internal developer tools that automate debugging, testing, and deployment processes
- High-scale ingestion pipelines processing large volumes of live data
- Monitoring systems that detect failures and proactively suggest fixes
What We’re Looking For:
- Experience building AI workflows, agents, or developer automation tools
- Strong background in distributed systems, backend infrastructure, or data pipelines
- Experience designing systems that run large volumes of automated jobs or integrations
- Exposure to LLM orchestration, AI tooling, or experimentation in this space
- A builder mindset — someone who has created systems, tools, or meaningful side projects
Ideal Profile:
- Enjoy building systems that eliminate repetitive engineering work
- Prefer infrastructure, tooling, and automation over traditional product features
- Move quickly, prototype often, and iterate based on real feedback
- Have hands-on experience with automation tools, scrapers, AI systems, or internal platforms
- Comfortable working in a fast-paced, early-stage environment with high ownership Tech StackGo, Python, TypeScript, Postgres, ClickHouse, AWS, and modern AI/LLM tooling
Why This Opportunity:
- High ownership — make real architectural decisions
- Work on systems that directly impact product performance and user outcomes
- Join a small, highly technical team solving complex real-time data problems
- Strong engineering culture focused on speed, quality, and impact
- Competitive compensation and meaningful equity
Interview Process:
- Intro call with the team
- Take-home challenge (practical, under 2 hours)
- Systems design discussion
- Final conversation with leadership
If you’re interested in building AI-driven systems in a real-time, high-scale sports data environment, this is a great opportunity to explore.
Please send your resume in Word format to Ian Ascuasiati at ian.ascuasiati@quantum-qtr.com.
REFER A NEW HIRE AND EARN A CASH BONUS! For details, click here.
All applications are reviewed by our recruitment team, and hiring decisions are made by people. We may also use AI-enabled tools to support parts of the application review process.