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Added 5 months ago
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AI Engineer
Portless
Remote, Canada
- Remote
Collaborate closely with product, operations, and engineering teams to identify high-leverage AI opportunities and deliver them end-to-end
Added 5 months ago
Senior Data Platform Engineer
Helcim Inc
Calgary, Alberta
Partner with the Staff Developer to drive technical design, balancing trade-offs and advising on complex cross-team data platforms.
Added 5 months ago
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Staff Machine Learning Engineer, AI Generation Engine
SandboxAQ
Remote, Canada
- $146,200 to $258,000 CAD / year
- Full-time
- Remote
Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives.
Added 5 months ago
S
Senior Machine Learning Engineer, AI Generation Engine
SandboxAQ
Remote, Canada
- $119,000 to $210,000 CAD / year
- Full-time
- Remote
Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives.
Added 5 months ago
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Senior Software Engineer, Builders
EvenUp
Remote, Canada
- Full-time
- Remote
Familiarity with Python, TypeScript, or the modern AI/ML stack
Added 4 months ago
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Senior Specialist, Data Modeler (Microsoft
Vale
Toronto, Ontario
- Full-time
…United Kingdom, and Japan. We invite you to use your skills with us and contribute to something meaningful and…
Added 5 months ago
MS
Senior Software Engineer - AI/Computer Vision (Camera Systems)
Motorola Solutions
Vancouver, British Columbia · Toronto, Ontario
- Full-time
At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We…
Added 5 months ago
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Intermediate Software Engineer
AltaML
Calgary, AB · Edmonton, AB · Toronto, ON
- Full-time
…about AI/ML, thrive in a dynamic environment, and want to work with a diverse team of wickedly smart people, we want to hear from…
Added 5 months ago
Manager, Financial Planning and Analysis
Benevity
Canada
Proven technical development and AI competencies (e.g., Python, SQL, AI/ML tools), with a strong track record of modernizing finance operations and reducing spreadsheet reliance.
Added 5 months ago
Manager, Financial Planning and Analysis
Benevity
Calgary, Alberta
Proven technical development and AI competencies (e.g., Python, SQL, AI/ML tools), with a strong track record of modernizing finance operations and reducing spreadsheet reliance.
Added 5 months ago
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Member of Technical Staff
Beacon Software
Toronto, Ontario
- Full-time
We are building that system. A cross-portfolio data lake on open table formats, with a feature store on top that makes the data agent-readable. An action layer that runs workflows across…
Added 5 months ago
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Senior Specialist, Data Modeler – OT & Industrial Automation
Vale
Greater Sudbury, Ontario
- Full-time
…United Kingdom, and Japan. We invite you to use your skills with us and contribute to something meaningful and…
Added 5 months ago
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AI Engineer - Remote
Huzzle
Remote, Canada
- Full-time
- Remote
Strong experience with Python and AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, or LangChain.
Added 5 months ago
CP
Data Architect | Canada
Cuesta Partners
Remote, Canada
- $180,000 to $225,000 CAD / year
- Full-time
- Remote
Cuesta Partners is looking for a Data Architect to engage with us on transformational data programs with companies looking to take their AI & data capabilities to the next level.
Added 5 months ago
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Applied AI Scientist (Hybrid)
Homebase
Remote, Canada
- $108,000 to $130,000 CAD / year
- Full-time
- Remote
At Homebase, you’ll join a team that’s bold, fast-moving, and obsessed with helping small businesses thrive. We build with empathy, act with urgency, and take big swings that drive…
Added 5 months ago
T
Applied Scientist, Pro Growth
Thumbtack
Remote, Canada
- Full-time
- Remote
We’re looking for applied scientists with deep expertise in machine learning, optimization, building data products, and/or statistical models. As part of a small product team you will have…
Added 5 months ago
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Software Dev QA Specialist
Fortinet
Burnaby, BC
- Full-time
Reproduce and troubleshoot bugs with developers to ensure defects are correctly identified and resolved.
Added 5 months ago
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Associate AI Engineer
ShyftLabs
Toronto, Ontario
- Full-time
Proficiency in Python and familiarity with libraries or frameworks such as TensorFlow, PyTorch, or Scikit-learn
Added 5 months ago
LS
AI Toolchain Software Developer
Lattice Semiconductor
Montreal, Quebec
- Full-time
Proficiency in Python, with the ability to write clean, maintainable code for both prototyping and production environments.
Added 5 months ago
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Senior Software Developer, Data & MLOps
OSEDEA
Montreal, Quebec
- Full-time
As a Senior Software Developer with strong Data Engineering and MLOps experience, you design, build, and deliver robust data and machine learning solutions for our clients. You combine…
Added 5 months ago
S
Senior Software Engineer II
SurveyMonkey
Remote, Canada
- $126,400 to $158,000 CAD / year
- Full-time
- Remote
Expert-level Python skills and experience with high-scale data processing (PySpark, etc.).
Added 5 months ago
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Security Researcher
Fortinet
Burnaby, British Columbia
- Full-time
Join Fortinet, a cybersecurity pioneer with over two decades of excellence, as we continue to shape the future of cybersecurity and redefine the intersection of networking and security. At…
Added 5 months ago
SA
Staff Research Scientist, Dexterous Manipulation
Sanctuary AI
Vancouver, British Columbia
- Full-time
…the exclusive chance to make a meaningful impact by working with novel haptic and proprioceptive sensing techniques, thanks to our in-house robot with dexterous…
Added 5 months ago
SA
Machine Learning Research Intern (Reinforcement/Imitation Learning)
Sanctuary AI
Vancouver, British Columbia
- Internship
…and machine learning skills as well as hands-on experience with robotics. In this role you’ll be a valued contributor and you’ll gain a comprehensive understanding of the design,…
Added 6 months ago
T
Machine Learning Engineer II
TD
Remote, Canada
- Full-time
- Remote
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Beacon Software

Member of Technical Staff

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: May 19, 2026

Original job description

About Beacon Software

Beacon is acquiring and operating a portfolio of vertical SaaS companies. Most private equity firms scale by adding people. We are building Beacon to scale by adding software. The thesis is simple: portfolio operations, value creation, and deal sourcing are bottlenecked by human attention, and an agentic operating system can lift that ceiling by an order of magnitude.

We are building that system. A cross-portfolio data lake on open table formats, with a feature store on top that makes the data agent-readable. An action layer that runs workflows across three domains: how we run the portfolio, how we grow the portfolio, and how we acquire into it. A feedback loop underneath that captures every action and outcome with stable identifiers. By the next phase of buildout we will have 100+ portfolio companies running on this platform. That is a problem set with serious data scale, real multi-tenant isolation requirements, and very few precedents to copy from.

About the Role

Members of Technical Staff (MTS) are the senior engineers who build the platform that everything else at Beacon runs on. You will own a piece of the core stack end-to-end: design, implementation, operations, and the long-term technical direction of that area. This is a Staff Engineer role in everything but name. We run flat.

The work is systems engineering at its core. Multi-tenant data infrastructure across very different portcos. Event-driven pipelines that have to be correct under partial failure. Service architectures that have to stay simple as the product surface grows. APIs and SDKs that other engineers - including FDEs out in the field - will build on every day. ML and agentic systems are part of the stack. They sit on top of a foundation that has to be solid first.

This is not infrastructure for its own sake. The platform has to be solid before anything else at Beacon works. That is the job.

What You'll Do

You will own one of these areas end-to-end:

Data platform. The cross-portco data lake on Iceberg with Snowflake or Databricks as the query engine. Per-portco S3 and KMS isolation. The ingestion pipeline from QuickBooks, HubSpot, Salesforce, PostHog, Intercom, Linear, Slack, Gmail, Postgres, Stripe, Zendesk, and our internal tools. The canonical data model that survives contact with very different portcos. The catalog and semantic layer on top so a query like "show me sales across all portcos" actually resolves.
Core services and APIs. The backend services that everything else at Beacon depends on: identity, access control, audit, workflow orchestration, the internal APIs that FDEs and ops engineers build against. The bar here is not novelty. It is correctness, latency, observability, and the kind of API design that ages well.
Multi-tenant isolation. Per-portco data, compute, and credential boundaries. Cross-cloud (AWS and Azure) connectivity. Regional residency for portcos in regulated verticals. This is the unglamorous infrastructure work that determines whether we can onboard portco 50 as fast as portco 5.
Workflow and action runtime. The execution layer that runs operational workflows across the three domains. Typed action surfaces, idempotency, retries, rollback paths, human-in-the-loop approval gates, audit trails. Some workflows are scripted. Some are model-driven. The runtime treats them as variations of the same primitive.
Observability and evals. The harness that tells us whether the system is working: traces, metrics, structured logs, replay infrastructure, regression suites, the ability to safely A/B-test changes across the portfolio. Both for traditional services and for model-driven workflows.
Safety and blast radius. Wrong actions against a portco's customers, revenue, or product are the worst kind of mistake we can make. Designing the autonomy tiers, the kill switches, the per-action-class blast-radius caps, and the audit surfaces is foundational platform work, not an afterthought.

Who You Are

Senior engineering depth. Staff or principal-equivalent. You have built and operated systems that real businesses depend on. You write clean, idiomatic code in at least one of Python, Go, Rust, or TypeScript, and you can work in any of them. You have an opinion on how to structure a service and you can defend it without raising your voice.
Distributed systems intuition. You have lived through enough production incidents to know where things actually break. Idempotency, partial failure, retry semantics, eventual consistency, schema evolution, multi-tenant isolation. These are not concepts you read about. They are things you have debugged at 2am.
Data infrastructure experience. You have built or operated something non-trivial on a modern data stack: Kafka, Spark, dbt, Iceberg, Snowflake, Databricks, BigQuery, or comparable. You understand the difference between a warehouse and a lake, and when each is the right answer.
Platform mindset. You build for the engineer two seats over as much as for the end user. Your APIs are easy to use correctly and hard to use incorrectly. You write the documentation. You make the migration path obvious. You treat developer experience as a feature, not a chore.
Comfortable with ambiguity. The product surface and the scope of the platform are still being defined. You will be making decisions in week 1 that constrain what is possible in year 3. You need to be the kind of engineer who is energized by that, not paralyzed by it.
Interest in modern ML, not necessarily expertise. You do not need to be an ML researcher. You need to be the kind of engineer who can read a paper, build the infrastructure around a model someone else trained, and have an informed opinion on where ML belongs in the stack and where it does not. If you have shipped LLM-driven systems in production, that is a plus, not a requirement.

Bonus Points

Prior Staff or Principal Engineer experience at a high-bar engineering org.
Experience with Iceberg, Polaris, Snowflake, or Databricks at scale.
Multi-tenant SaaS or platform infrastructure background.
Production experience with LLM-driven systems, including evals and observability.
Background in offline RL, contextual bandits, or sequential decision-making (for the applied research workstreams).
Open-source contributions to data infrastructure, observability, or developer tooling projects.

Our Values at Beacon Software

Humility: We acknowledge that the path to getting to the right answer involves being wrong along the way. We have strong beliefs which are weakly held. We actively seek new ideas and believe we can learn from anyone at any time.
Honesty: We are truth seeking in our approach to business problems. Business is a repeat game and we believe that human relationships generate alpha. We understand that trust is earned over a lifetime and can be lost in an instant.
Hunger: We play to win. We hold ourselves to high standards and will not be outworked. We take pride in having a deep sense of responsibility to ourselves, each other, our partners, and our customers. We believe to whom much is given much is expected.
Horizon: We seek to build a generational software company. This will take decades. We manage our expectations and those of our partners to take advantage of the 8th wonder of the world - compounding growth.

How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Beacon Software uses Artificial Intelligence and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.

AI does not make hiring decisions: Every application is reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate.

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More about this job

Responsibilities

Design and implement the core platform infrastructure, including a cross-portfolio data lake and multi-tenant service architectures. Own the end-to-end technical direction of critical areas such as data ingestion, workflow runtimes, and system safety.

Requirements

Requires senior-level engineering depth equivalent to a Staff or Principal Engineer with extensive experience in distributed systems and modern data stacks. Must be proficient in Python, Go, Rust, or TypeScript and comfortable managing ambiguity in a fast-paced environment.

Skills

Systems Engineering
Distributed Systems
Multi-tenant Architecture
Data Infrastructure
API Design
Python
Go
Rust
TypeScript
Iceberg
Snowflake
Databricks
Kafka
Spark
LLM Infrastructure
Observability

Visa sponsorship

Not detected in the job text

Keywords

SaaS
Data Lake
Iceberg
Snowflake
Databricks
Multi-tenancy
Distributed Systems
Python
Go
Rust
TypeScript
Kafka
Spark
dbt
BigQuery
LLM
Agentic Systems
API Design
S3
KMS
Workflow Orchestration
Observability
Idempotency
Event-driven Pipelines
Cloud Connectivity
AWS
Azure
Semantic Layer
Data Modeling
Systems Engineering

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