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Added 5 months ago
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Senior Site Reliability Engineer
SimCorp
Toronto, Ontario
- Full-time
As a Senior Site Reliability Engineer, you will be embedded within one of our Product Areas, taking ownership of specific responsibility domains where your experience, interests, and growth…
Added 2 months ago
Software Engineer, Platform Operations
Planet
Canada
A Software Engineer in Platform Operations is responsible for helping design, build, and operate the core infrastructure that enables Planet's engineering teams to reliably deploy and scale…
Added 5 months ago
MS
Senior Software Engineer - AI/Computer Vision (Camera Systems)
Motorola Solutions
Vancouver, British Columbia · Toronto, Ontario
- Full-time
As a Senior Software Engineer in our camera systems group, you will play a crucial role in designing, developing, and optimizing C++ code for embedded systems. You will work on implementing…
Added 5 months ago
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Intermediate Software Engineer
AltaML
Calgary, AB · Edmonton, AB · Toronto, ON
- Full-time
The Intermediate Software Engineer independently owns and delivers well-defined, small-to-medium complexity user stories end to end. You work AI-first by default - using Claude Code and…
Added 5 months ago
GE
Senior Data Engineer
GFL Environmental Inc.
Vaughan, Ontario
- Other
Our GFL team is expanding, and we are seeking a highly skilled Senior Data Engineer with experience in designing and maintaining real-time data streaming pipelines and building robust data…
Added 5 months ago
BS
Member of Technical Staff
Beacon Software
Toronto, Ontario
- Full-time
…long-term technical direction of that area. This is a Staff Engineer role in everything but name. We run…
Added 5 months ago
BS
Forward Deployed Engineer
Beacon Software
Toronto, Ontario
- Full-time
A strong generalist engineer. You can ship full-stack TypeScript or Python on the backend, React on the frontend, SQL fluently, comfortable in someone else’s codebase within a day. You do…
Added 5 months ago
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Principal/Senior Software Engineer
PointClickCare
Mississauga, Ontario
- Full-time
Added 5 months ago
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Senior Engineer – Digital Distribution & Engagement
Invesco Ltd.
Charlottetown, Prince Edward Island
- Full-time
…frameworks. The position requires a strong technical hands-on-skilled engineer. A successful candidate must demonstrate strong analytical, design, programing, and debugging skills in a…
Added 5 months ago
TA
Forward Deployed Engineer (Generative AI)
Tiger Analytics Inc.
Remote, Canada
- Full-time
- Remote
Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring…
Added 5 months ago
TA
Forward Deployed Engineer (Generative AI)
Tiger Analytics Inc.
Remote, Canada
- Full-time
- Remote
Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring…
Added 4 months ago
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Engineering Manager, Data AI & Analytics
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Toronto, Ontario
- Full-time
- Other
Reporting to the Director of Platform Engineering, Data AI & Analytics, the Data Engineer Manager leads and develops a team of Data Engineers while remaining hands-on in the delivery of…
Added 5 months ago
Robotics - Software Development Engineer
Amazon
Toronto, Ontario
- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design
Added 4 months ago
C
Systems Engineer
CAE
Montreal, Quebec
- Full-time
Added 4 months ago
AI Developer/Prompt Engineer
Levio
Toronto, Ontario
We are seeking AI Developer /Prompt Engineer to contribute to major projects.
Added 5 months ago
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AI Engineer - Remote
Huzzle
Remote, Canada
- Full-time
- Remote
We are looking for a skilled AI Engineer with at least 2 years of hands-on experience in developing, deploying, and optimizing AI and machine learning solutions. You will work closely with…
Added 5 months ago
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Product Engineer (Pharma)
Basetwo
Remote, Canada
- Full-time
- Remote
We’re hiring a Product Engineer to work closely with pharmaceutical and chemical manufacturing customers to deploy AI-powered solutions in real lab-scale and GXP environments.
Added 5 months ago
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Applied Scientist, Pro Growth
Thumbtack
Remote, Canada
- Full-time
- Remote
3+ years of industry experience as an applied scientist, data scientist, or ML engineer with ownership of production ML models.
Added 5 months ago
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Automation Engineer - Workflow & Process Automation
Huzzle
Remote, Canada
- Full-time
- Remote
We’re hiring a skilled Automation Engineer to help design, build, and optimize scalable workflows that improve business efficiency and eliminate repetitive tasks. This is a great…
Added 5 months ago
S
Associate AI Engineer
ShyftLabs
Toronto, Ontario
- Full-time
ShyftLabs is looking for an Associate AI Engineer (New Grad) to join our growing engineering team. This is an exciting opportunity for a recent graduate or early-career engineer who wants…
Added 6 months ago
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Go-to-Market Engineer
atqleads
Remote, Canada
- Contract
- Remote
The GTM Engineer is the engine builder at the core of every ATQ Squad engagement.
Added 5 months ago
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Software Engineer, Detection (TOR)
Doppel
Toronto, ON
- $157,000 to $367,000 CAD / year
- Full-time
Strong mastery of at least one backend language (Python, Go, Java, or Node) and comfort with web APIs, async processing, and service frameworks.
Added 2 months ago
Sr. Staff Physical Design Timing Engineer (STA)
Lightmatter
Toronto, ON
We are hiring a Physical Design Timing Engineer to help drive backend digital execution for some of the leading photonics based interconnect solutions. You will work alongside a team of…
Added 2 months ago
Data Platform Operations Engineer
Scotiabank
Toronto, ON
The Data Platform Operations Engineer will play a critical role within the Enterprise Data & AI Technology organization - one of Scotiabank’s most significant enterprise-wide strategic…
Added 5 months ago
Network Engineer, Foundation and Support (Edge/Backbone Infrastructure Design)
Meta
Quinte West, Ontario
…this role, we are looking for a Network Infrastructure Design Engineer with demonstrated experience in developing and delivering network infrastructure solutions at scale in a data center…

Beacon Software

Member of Technical Staff

Toronto, ON, Canada

Full-time

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Applications open in a new tab.

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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