Required:

• 3+ in Windows desktop application development using Windows App SDK, WinUI (or similar), C#, XAML — and ideally additional experience with native Windows code (C++, Win32/WinRT/COM).
• Deep understanding of Windows application architecture, including interop between managed code (.NET) and native code.
• Proven track record of designing, building, and shipping production-quality desktop applications, with an emphasis on reliability, performance, scalability, and maintainability.
• Strong experience with accessibility APIs on Windows (e.g. Microsoft UI Automation or similar), and a dedication to building accessible and inclusive software.
• Excellent software engineering fundamentals: OOP, design patterns, data structures, algorithms, memory management, multi-threading or asynchronous programming (where relevant).
• Experience leading technical design, mentoring other engineers, conducting code reviews, and making architecture-level decisions.
• Strong communication skills; ability to articulate tradeoffs, collaborate with cross-functional teams, and drive consensus.
• A user-centric mindset: focus on building polished, intuitive, and accessible experiences for end users.

Preferred / Bonus:

• Experience with writing automated tests for UI — unit tests, integration tests, UI automation tests; familiarity with relevant testing frameworks.
• Experience with performance optimization for desktop apps (memory usage, startup time, rendering performance, high-DPI support, responsiveness under load).
• Experience with localization/globalization, right-to-left UI support, internationalization, accessibility for multiple regions.
• Familiarity with telemetry, analytics, crash reporting, logging, and error monitoring in desktop applications.
• Previous experience in shaping CI/CD workflows, release pipelines, and deployment strategies for desktop applications.
• Demonstrated ability to take ownership of feature areas or modules and drive them long-term, including maintenance, refactoring, and technical debt management.

What we offer

• A high-impact role: you will define architecture, shape the future of our Windows product, and directly influence what millions of users see and experience.
• A collaborative, flat-structure engineering culture — you are not just a coder, but a builder and a decision-maker.
• Opportunities to lead — mentor others, steer technical direction, and grow into broader technical leadership (e.g. Tech Lead, Architect).
• Flexibility, autonomy, and responsibility: you define how to solve problems, own features end-to-end, and contribute to long-term product vision.
• A purpose-driven mission: building software that’s reliable, accessible, and user-centered — making a real difference for people.                  

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 
Refer them! 

Speechify is committed to a diverse and inclusive workplace. 
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

About Behavox

Behavox is a cloud-native AI company providing an integrated controls platform for global banks, asset managers, hedge funds, private equity firms, insurance businesses, and commodity firms. The platform unifies communications and trade surveillance, compliant archiving, policy management as well as front-office analytics on a single, AI-native technology stack, delivered as a globally scalable SaaS-based cloud service.

At Behavox, our engineering culture is built around speed, experimentation, and technical excellence, following agile principles and rapid iteration. We constantly test and adopt the latest cloud technologies and AI tooling, optimising for fast feedback loops and execution. We look for people who can move fast, challenge conventional wisdom, and who want to work at the frontier of modern AI, SaaS platforms, and distributed systems.

Behavox is a high-performance organisation with a strong bias toward delivery, ownership, and responsibility. We commit, and we execute. We are building systems that are complex, mission-critical, and global in scale; systems that many consider too large or too difficult. To do that, we seek the smartest, most technically capable engineers and technologists who take end-to-end responsibility and want to win by building what others cannot.

Founded in 2014 and backed by SoftBank Vision Fund, Behavox is headquartered in London, with offices worldwide, including New York City, Montreal, Seattle, Singapore, and Tokyo.

About the Role

The Software Engineer (Java) operates at a senior engineer level, driving technical direction across core product domains. The role combines deep hands-on Java engineering with architectural ownership — from high-level system design and technology selection to leading delivery of critical, cross-cutting platform capabilities.

At this level, engineering excellence extends beyond implementation: the engineer determines the right approach to complex problems, communicates technical decisions across functions, participates in hiring, and is accountable for the long-term health of the systems they own. This level demands sound judgment on technology and business trade-offs and the ability to act as a technical lead. A defining expectation is mastery of AI-assisted engineering — leveraging agentic AI tools as force multipliers while retaining full ownership of architecture, quality, and technical outcomes.

What You'll Bring

• Expert Java engineering: Deep understanding of Java internals — GC tuning, Collections Framework, advanced concurrency (java.util.concurrent, multithreading), NIO/NIO2, performance profiling, and heap-dump analysis. Mastery of Spring Framework (IoC/DI, bean lifecycle, Spring Boot). SOLID principles, Clean Code practices, and GoF design patterns
• Software architecture and design patterns: Expertise in monolith and microservices architectural styles — including migration patterns and domain-driven decomposition. Inter-process communication design (REST, gRPC, messaging), transaction management in distributed systems (Sagas, 2PC), CQRS, Event Sourcing, and external API design focused on scalability, security, and documentation
• Cloud-native platforms and infrastructure: Experience designing high-availability and high-load systems on GCP (preferred), AWS, and Azure. Cloud security best practices: IAM, VPC, data encryption, JWT/JWS/JWE. Infrastructure as Code (Terraform or equivalent) and Twelve-Factor App methodology
• Observability, reliability and deployment: Implementing full observability stacks: structured logging, distributed tracing, metrics, and alerting. SLI/SLO/SLA frameworks. Deployment strategies: Rolling Updates, Blue/Green Deployments, Canary Releases
• AI-assisted engineering: Practitioner-level command of agentic AI tools applied to software engineering — encompassing prompt engineering techniques, AI context management and its limitations, sub-agents, skills and plugins, multi-agent orchestration, and team-of-agents architectures. Experience with Claude Code (Anthropic), Codex (OpenAI), or equivalent is mandatory

What You'll Do

• Architecture and technology leadership: Lead high-level design for complex, cross-service features. Evaluate and select appropriate technologies, frameworks, and architectural patterns before delegating implementation. Produce and maintain architecture documentation: design docs, ADRs, tech specs, and wiki pages
• Advanced Java feature implementation: Own and implement critical product components — including prototyping, architecture validation, and production-grade code. Ensure correctness, performance, and long-term maintainability with comprehensive test coverage (unit, integration, contract, component)
• Technical roadmap contribution: Drive the engineering agenda for assigned product areas. Proactively identify gaps in requirements, architectural limitations, and technical risks. Contribute to product roadmap planning and delivery estimation. Participate in hiring processes
• Cross-functional technical communication: Drive technical communication across engineering, product, DevOps, and ML teams. Communicate technical decisions clearly to non-technical stakeholders. Produce design documents and participate in tech talks and knowledge-sharing sessions
• AI-augmented engineering: Direct agentic AI tools (Claude Code, Codex, or equivalent) across the full engineering workflow — code generation, testing, refactoring, debugging, and documentation. Demonstrated ability to apply advanced prompt engineering, manage AI context limitations, compose multi-agent orchestration workflows, and critically evaluate AI-generated outputs for correctness, security, and quality. Ability to establish guardrails and improve agent configurations to raise the quality bar. AI proficiency amplifies — it does not replace — deep engineering judgment and technical accountability

What We Offer

• The opportunity to work on a global, mission-critical AI platform alongside the best engineers and technologists across multiple geographies
• A role with real ownership and impact, building complex systems at scale in an environment that values speed, experimentation, and technical excellence
• A highly attractive benefits package, including competitive cash compensation, an equity award aligned with long-term value creation, and comprehensive health insurance for employees and their families
• Modern, comfortable offices in Montreal/ Toronto downtown, with an expectation of working from the office 1 day per week, reflecting our belief in strong in-person collaboration, while remaining flexible to accommodate remote work for candidates who live in other Canadian cities
• A generous time-off policy of 30 days annually, plus public holidays and sick leave, recognising the importance of sustained high performance

About Our Process

Our selection process is designed to rigorously assess a candidate’s depth of technical knowledge, problem-solving ability, and alignment with Behavox’s mission and core values.

As part of the process, candidates will first participate in a series of interviews focused on evaluating their technical expertise and engineering judgment. Candidates who successfully progress through these interviews will then be invited to complete a live technical exercise. The purpose of this live technical assessment is to validate the candidate’s stated technical competencies and assess their ability to solve complex problems with speed, accuracy, and sound engineering judgment. Note that whenever possible, we aim to conduct interviews in person at our offices.

We recognise and respect the time candidates invest in this process. In return, Behavox commits significant time and resources to ensure that those who join us have the capability, judgment, and alignment required to operate at the speed and level of complexity our work demands. We value efficiency and clarity on both sides; if at any point we determine that a candidate is not a fit, we reserve the right to immediately conclude the interview or the technical assessment.

Please note the following:

• A core objective of the process is to objectively assess individual knowledge and competencies. The use of AI tools or external assistance during live interviews or technical exercises is strictly prohibited (unless explicitly instructed otherwise) and will result in immediate disqualification.
• Interviews and technical sessions may be recorded for internal review to support fairness, consistency, and collaborative decision-making within the hiring team.

Data Platform Solution Architect

Who We Are: 

Quadbridge is a fast-growing North American IT solutions provider, empowering businesses to navigate complex challenges daily, through strong partnerships with leading technology providers and close collaboration with our team and customers.

With locations in Kitchener, Montreal and Vancouver, we strive to create an energetic, fun workplace where ambitious, like-minded teammates collaborate, innovate, and thrive as we continue to grow our national footprint.

We are Quadbridge. See how we’re building tomorrow’s solutions, together.

This Role:

We are seeking a mid‑level Data Platform Solution Architect to join our consulting and professional services team.

This role blends solution architecture, pre‑sales support, and delivery execution, focused on designing and implementing modern data and AI platforms using Microsoft Fabric and Azure Databricks.

The successful candidate will work closely with pre-sales & delivery teams to drive assessment‑led engagements, build scalable data platform & AI design and architectures, and accelerate customer outcomes while enabling downstream services and managed services attach.

Key Responsibilities

Solution Architecture & Design

• Architect modern Data & AI platforms (Lakehouse/Data Lake) and analytics platforms using:
• Microsoft Fabric (OneLake, Data Engineering, Data Factory, Data Science, Real‑Time Analytics, Power BI)
• Azure Databricks (Lakehouse, Delta Lake, Workflows, Unity Catalog)
• Design secure, scalable, and cost‑optimized Data & AI platform architectures aligned to SMB and mid‑market needs
• Develop reference architectures and repeatable patterns aligned to Microsoft and Databricks best practices

Pre‑Sales & Assessments

• Support pre‑sales activities including:
• Technical discovery sessions
• Architecture whiteboarding
• Scoping and estimation support for Statements of Work (SOWs)
• Lead or contribute to Data & AI platform assessments (Data & AI Readiness, Fabric Readiness, Databricks/Lakehouse Assessments)

Delivery & Technical Leadership

• Act as technical lead or senior contributor on data platform implementations
• Provide design oversight and hands‑on guidance for:
• Data ingestion pipelines
• Data source integrations
• Transformations (SQL, PySpark)
• Semantic models and analytics layers
• Ensure delivery aligns to scope, timelines, and architectural standards

Governance, Security & Optimization

• Design data governance, security, and compliance models including:
• Data access controls
• Cataloging and lineage
• Workspace and tenant design
• Apply FinOps and performance optimization practices to control cloud costs
• Advise clients on platform lifecycle management and operational readiness

Partner & Practice Enablement

• Stay current with Microsoft Fabric and Databricks roadmaps and partner best practice guidance
• Contribute to:
• Internal accelerators
• Delivery templates
• Sales enablement content
• Support partner motions aligned to Microsoft Solution Partner and Databricks designations

Required Qualifications

Technical Experience

• 4–6 years of experience in data & AI engineering, analytics, or data platform architecture
• Hands‑on experience with:
• Microsoft Fabric or strong Azure Data + Power BI background transitioning to Fabric
• Strong Copilot/Copilot Studio background
• Azure Databricks and or Databricks
• Strong understanding of:
• Data platform & AI Lakehouse architecture
• ELT/ETL patterns
• SQL and PySpark
• Experience with Azure data services such as:
• Azure Data Lake Storage
• Azure Synapse
• Azure SQL
• Azure Data Factory

Consulting & VAR Experience

• Experience in a VAR, systems integrator, or consulting environment

Communication & Collaboration

• Strong client‑facing consulting and communication skills
• Ability to translate technical concepts into business value
• Experience collaborating with sales, delivery, and pre-sales teams

Preferred Certifications

Microsoft (preferred)

• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert (plus)

Databricks

• Databricks Data Engineer Associate
• Databricks Data Engineer Professional
• Databricks Lakehouse Fundamentals

Cloud & Architecture (Nice to Have)

• Azure Fundamentals (AZ‑900)
• AI‑900 (Azure AI Fundamentals)
• FinOps Practitioner (or equivalent cost‑management training)

What Success Looks Like (First 12 Months)

• Successfully support and deliver multiple Fabric and Databricks engagements
• Become a trusted technical advisor to sales and clients
• Drive assessment‑led opportunities into implementation and managed services
• Contribute to repeatable offerings that improve delivery margin and velocity

Why Quadbridge? 

• Invest in Your Future – Benefit from our RRSP program to help you plan ahead.
• Grow With Us – Take advantage of ongoing professional training and development opportunities.
• Comprehensive Coverage – A complete health, dental, life and LTD insurance plan
• Top-Tier Equipment – We provide everything you need to do your best work.
• A Vibrant Workplace – Join us for monthly social and team building events.
• Perks You’ll Love – In our Montreal office, enjoy an onsite chef and gym.
• Stay Connected – Receive a phone allowance to keep you plugged in.
• Bring Your Best Friend – Our offices are pet-friendly!

Salary range

$160,000 to $185,000 annually, plus bonus based on KPIs

Work Schedule:

Monday to Friday, 8:30 a.m. to 5 p.m.

Permanent, full-time, hybrid or remote

Location:

Montreal (QC) , Kitchener (ON) or Vancouver (BC)

Application Deadline  

June 30, 2026

Ce poste est également affiché en français. 

Quadbridge is an equal opportunity employer, committed to diversity and inclusion in compliance with the Canadian Human Rights Act and Employment Equity Act. If you require accommodations under the Accessibility for Ontarians with Disabilities Act (AODA) and other applicable Canadian laws during the interview process, please inform us, and we will ensure your needs are met.

We are seeking a Senior DevOps & Site Reliability Engineer to own the reliability, scalability, performance, and operational excellence of Medeloop’s platform. This role blends deep DevOps engineering—CI/CD pipelines, infrastructure as code, and cloud architecture—with SRE discipline: SLOs, incident management, capacity planning, observability and a relentless focus on system uptime. You will be the bridge between development and operations, ensuring our clinical research products are always available, performant, and secure for the healthcare organizations that depend on them.

What You'll Own

Cloud Infrastructure & Architecture

• Design, implement, and manage scalable, secure, and highly available cloud infrastructure on AWS - infrastructure as code (IaC) using AWS CDK, CloudFormation, or Terraform, ensuring all environments are version-controlled and reproducible.
• Architect multi-region and disaster recovery strategies that meet healthcare uptime requirements.
• Manage containerized workloads using Docker and Kubernetes, optimizing for cost, performance, and resilience.

Site Reliability Engineering

• Define, implement, and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs) across all production services.
• Build and maintain observability stacks (DataDog, AWS CloudWatch, Sentry) covering metrics, logs, traces, and alerting.
• Lead incident response: triage, mitigate, and drive blameless post-incident reviews with actionable follow-ups.
• Conduct capacity planning and performance engineering to ensure the platform scales ahead of demand.
• Champion error budgets and use them to balance feature velocity with system stability.
• Identify, assess, and mitigate operational risks by collaborating with engineering and product teams to evaluate impact and likelihood before they become incidents.
• Participate in and help structure an on-call rotation, ensuring clear escalation paths and fair distribution of after-hours coverage.

CI/CD & Automation

• Build self-service tooling and runbooks that reduce toil and empower development teams to ship independently.
• Design and maintain CI/CD pipelines (GitHub Actions) that enable fast, safe, and repeatable deployments.
• Automate security scanning (SAST, DAST) within pipelines and collaborate with engineering to remediate findings.
• Implement progressive delivery strategies such as canary deployments, blue-green releases, and feature flags.
• Proficiency in scripting languages (Python, Bash) for automation, troubleshooting, and building reliability tooling.
• Track and drive down operational toil, targeting less than 50% of team time spent on repetitive manual work.
• Evaluate and manage change risk for production deployments, maintaining change review processes that balance speed with stability.

Security & Compliance

• Ensure infrastructure meets healthcare compliance standards (HIPAA, SOC 2) through policy-as-code, encryption, and access controls.
• Manage networking security (VPCs, subnets, security groups, WAFs) and identity/authentication systems (AWS Cognito, Auth0, OAuth2, SSO).
• Conduct regular security reviews, vulnerability assessments, and patching across the infrastructure estate.

Collaboration & Culture

• Partner closely with product and engineering teams to embed reliability thinking into the software development lifecycle.
• Develop and maintain comprehensive documentation for infrastructure, runbooks, and operational playbooks.
• Mentor junior engineers on DevOps and SRE best practices, fostering a culture of ownership and continuous improvement.
• Stay current with advancements in cloud technologies, DevOps tooling, and SRE methodologies.
• Own and evolve internal developer platform tooling — including deployment workflows (GitOps/Flux), bug tracking integrations, and developer self-service portals.

What We're Looking For

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 7+ years of combined experience in DevOps and/or Site Reliability Engineering roles, with at least 2 years in a senior capacity.
• Deep proficiency with AWS services
• Deep experience with observability and monitoring platforms such as DataDog, AWS CloudWatch, and Sentry.
• Strong experience building and maintaining CI/CD pipelines with GitHub Actions or equivalent tools.
• Expertise in infrastructure as code using AWS CDK, CloudFormation, or Terraform.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Proven track record of defining and operating against SLOs/SLIs and managing incident response processes.
• Solid understanding of networking (VPCs, subnets, load balancing, DNS), security, and compliance best practices.
• Experience with authentication and authorization systems including AWS Cognito, Auth0, OAuth2, and SSO.
• Proactive, self-directed mindset with a bias toward action and taking initiative.
• Excellent problem-solving skills and the ability to work independently as well as collaboratively across teams.
• Strong communication skills—able to explain complex infrastructure decisions clearly to technical and non-technical stakeholders.
• Passion for unsolved challenges in healthcare AI, with the ability to thrive in a fast-paced, multidisciplinary environment and wear multiple hats.

Bonus Points

• Multi-cloud experience (AWS, Azure, GCP)
• Familiarity with healthcare data standards, compliance, and protocols such as HIPAA, HL7 FHIR, OMOP, and i2b2.
• Experience with chaos engineering practices and tools (e.g., AWS Fault Injection Simulator, Gremlin).
• Prior experience in a healthcare or life sciences company operating under strict regulatory requirements.
• Contributions to open-source infrastructure or SRE tooling.
• Relevant certifications such as AWS Solutions Architect, Certified Kubernetes Administrator (CKA), or Google SRE certification.

Why Medeloop

• Ownership from day one: small team, high-trust, no layers between your work and its impact
• Technically ambitious: you'll build AI-powered workflows, not just support them
• Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter
• Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build

The Role

This is a full-ownership data engineering role at the center of Medeloop's AI platform. You won't be maintaining pipelines someone else built,  you'll be architecting the data backbone that powers AI agents doing real operations at scale. You'll work directly with data scientists, AI engineers, and product teams to turn raw, complex healthcare data into the clean, structured, semantically-rich foundation our AI scientists depend on. Your work shows up in customer products and research outcomes, not internal dashboards that no one reads.Candidates who currently perform these tasks exclusively through manual processes are unlikely to be suitable for this role. We require an individual who has already adopted and integrated AI techniques to enhance operational velocity, rather than one who is contemplating future experimentation.If you want to build something that genuinely changes how medical research gets done, this is the role.

What You'll Own

• The healthcare data lake: curating, extending, and evolving it through new concepts, derived variables, and data models that directly inform our AI engines and customer products
• AI-native data workflows: designing and operating AI-powered pipelines (using tools like Claude Code and agent frameworks) to automate harmonization, cleaning, quality checks, and summarization at scale
• NLP and semantic infrastructure: building pipelines for entity extraction, concept normalization, embedding-based retrieval, and semantic search that power the AI Scientist platform
• Novel data extraction approaches: experimenting with and building new methodologies for working with unstructured clinical data, not just applying existing playbooks
• Research-grade data products: delivering analytical samples, cohorts, and final datasets that withstand scientific scrutiny and are actively used by researchers and customers
• Data governance and observability protocols: including access controls, PHI/PII handling, data classification, compliance, monitoring, alerting, data freshness, and comprehensive documentation to enable self-service capabilities.

What We're Looking For

• 3+ years of relevant data engineering or data management within an analytics-driven organization, with end-to-end ownership from raw ingestion to final data product
• Deep hands-on experience with healthcare CDMs (OMOP, FHIR, PCORnet) — designing or extending them, not just querying
• Knowledge of medical ontologies: UMLS, SNOMED CT, RxNorm
• Experience with big data, data pipelines and tooling that support retrieval-augmented generation (RAG), vector integrations, embedding workflows, and other AI/ML workloads. Experience in big data tooling such as Spark, Iceberg, EMR
• Fluent in Python and SQL; comfortable across structured and unstructured data
• Proven NLP experience: semantic search, entity recognition, concept normalization, embedding pipelines
• Strong grasp of inferential statistics and cohort methodology to be a real partner to data scientists and customers (as part of onboarding)
• Experience contributing to an AI/ML product, especially in automated research or scientific discovery
• Experience mentoring other engineers and providing technical leadership

Bonus Points

• Multi-cloud experience (AWS, Azure, GCP)
• Authorship or contribution to peer-reviewed publications or technical reports

Why Medeloop

• Ownership from day one: small team, high-trust, no layers between your work and its impact
• Technically ambitious: you'll build AI-powered workflows, not just support them
• Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter
• Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build