📍 Job Overview

Job Title: Senior Software Engineer (Biotech Cloud Infrastructure)
Company: Coders Connect
Location: Toronto, Ontario, Canada
Job Type: Full-Time
Category: DevOps Engineer, System Administrator, Web Infrastructure
Date Posted: June 25, 2025
Experience Level: 5-10 years
Remote Status: Hybrid (South San Francisco, California, United States or Toronto, Ontario, Canada)

🚀 Role Summary

Scalable Cloud Infrastructure: Maintain and scale cloud-based data pipelines in production, administer cloud infrastructure (AWS preferred) and GPU scheduling (e.g., RunAI).
Collaborative DevOps Support: Provide DevOps support to ML and research teams, collaborate with bioinformaticians, ML engineers, and scientists on complex data flows.
Scalable Software Systems: Build scalable software systems for high-throughput biological data analysis, ensuring system design supports big data environments.
Expertise in Python and Linux: Leverage strong Python skills and Linux proficiency to develop and maintain high-performance cloud environments.

📝 Enhancement Note: This role requires a balance of software engineering, data engineering, and infrastructure management skills, with a focus on cloud-based data pipelines and machine learning workflows.

💻 Primary Responsibilities

Cloud Infrastructure Management: Maintain and scale cloud-based data pipelines, administer cloud infrastructure, and manage GPU scheduling.
Collaborative DevOps Support: Provide DevOps support to ML and research teams, working closely with bioinformaticians, ML engineers, and scientists to ensure efficient data flows.
Scalable Software Systems: Design, develop, and maintain scalable software systems for high-throughput biological data analysis, ensuring system design supports big data environments.
Cross-Team Collaboration: Collaborate with various teams to understand their data processing needs, optimize workflows, and ensure data quality and integrity.
Technical Documentation: Document cloud infrastructure, data pipelines, and software systems to ensure knowledge sharing and easy onboarding of new team members.

📝 Enhancement Note: This role requires a strong understanding of cloud infrastructure, data pipelines, and software system design, with a focus on optimizing workflows and ensuring data quality and integrity.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: 5+ years of software engineering experience, with a focus on cloud infrastructure, data pipelines, and scalable software systems.

Required Skills:

Python (strong proficiency)
Linux (strong proficiency)
Cloud Services (AWS, GCP, or Azure)
Containerization (Docker)
Pipeline Orchestration (Metaflow, Snakemake)
Big Data Environments
Scalable System Design

Preferred Skills:

Background in bioinformatics or healthtech
Experience supporting regulated industries (e.g., life sciences)
Familiarity with R or data visualization in biology

📝 Enhancement Note: This role requires a strong technical skill set, with a focus on cloud infrastructure, data pipelines, and scalable software systems. Familiarity with bioinformatics or healthtech is a plus, but not required.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Cloud Infrastructure Projects: Showcase your experience in maintaining and scaling cloud-based data pipelines, with a focus on AWS, GCP, or Azure.
Data Pipeline Projects: Demonstrate your ability to design, develop, and maintain scalable software systems for high-throughput biological data analysis.
Collaborative Projects: Highlight your experience working with various teams to optimize workflows and ensure data quality and integrity.

Technical Documentation:

Cloud Infrastructure Documentation: Provide clear and concise documentation of your cloud infrastructure, including data pipelines, GPU scheduling, and any relevant configuration files.
Data Pipeline Documentation: Document your data pipeline projects, including data sources, processing steps, and output formats.
Software System Documentation: Document your software systems, including system design, codebase structure, and any relevant technical specifications.

📝 Enhancement Note: This role requires a strong portfolio demonstrating your experience in cloud infrastructure, data pipelines, and scalable software systems. Clear and concise technical documentation is essential for this role.

💵 Compensation & Benefits

Salary Range: CAD 120,000 - CAD 160,000 per year (based on market research for senior software engineering roles in Toronto with a focus on cloud infrastructure and data pipelines)

Benefits:

Unlimited PTO
Monthly lunch budget
Remote office setup stipend
Comprehensive medical, dental, and vision coverage for employees and dependents

Working Hours: 40 hours per week, with flexible hours to accommodate project deadlines and maintenance windows.

📝 Enhancement Note: The salary range for this role is based on market research for senior software engineering roles in Toronto with a focus on cloud infrastructure and data pipelines. Benefits are comprehensive and competitive, with a focus on work-life balance.

🎯 Team & Company Context

🏢 Company Culture

Industry: Biotech and AI-driven drug discovery, with a focus on leveraging real patient biology and AI to accelerate drug discovery.

Company Size: Medium-sized company with a hybrid work environment in South San Francisco, California, United States, and Toronto, Ontario, Canada.

Founded: The company was founded in 2020, with a mission to create one of the world's largest perturbation atlases to train next-generation foundation models.

Team Structure:

Data Engineering & Infrastructure: The team is responsible for maintaining and scaling cloud-based data pipelines, providing DevOps support to ML and research teams, and building scalable software systems for high-throughput biological data analysis.
Machine Learning & Research: The team is responsible for developing and implementing machine learning models and conducting research to advance the company's mission.
Bioinformatics: The team is responsible for analyzing and interpreting biological data, with a focus on mapping how therapies affect human cells in vivo.

Development Methodology:

Agile/Scrum: The team follows an Agile/Scrum methodology, with sprint planning, daily stand-ups, and regular retrospectives to ensure continuous improvement.
Code Review: The team follows a code review process to ensure code quality, with a focus on readability, maintainability, and performance.
CI/CD Pipelines: The team uses CI/CD pipelines to automate deployment and ensure consistent, reliable releases.

Company Website: www.codersconnect.co.uk

📝 Enhancement Note: The company culture is collaborative and innovative, with a focus on leveraging real patient biology and AI to accelerate drug discovery. The team structure is designed to foster cross-functional collaboration and ensure efficient data flows.

📈 Career & Growth Analysis

Web Technology Career Level: This role is a senior-level position, with a focus on cloud infrastructure, data pipelines, and scalable software systems. The role requires a strong technical skill set and a proven track record of success in a similar role.

Reporting Structure: The role reports directly to the Director of Engineering, with a dotted line to the Director of Data Science and the Director of Bioinformatics.

Technical Impact: The role has a significant impact on the company's ability to scale its data pipelines and support machine learning workflows in a high-performance cloud environment. The role requires a deep understanding of cloud infrastructure, data pipelines, and scalable software systems, with a focus on optimizing workflows and ensuring data quality and integrity.

Growth Opportunities:

Technical Leadership: As a senior member of the team, there is an opportunity to take on a technical leadership role, mentoring junior team members and driving technical decisions.
Architecture Decisions: The role has the opportunity to make architecture decisions that impact the company's ability to scale its data pipelines and support machine learning workflows.
Emerging Technologies: The role has the opportunity to stay up-to-date with emerging technologies in cloud infrastructure, data pipelines, and scalable software systems, and to incorporate them into the company's technology stack.

📝 Enhancement Note: This role offers significant growth opportunities, with a focus on technical leadership, architecture decisions, and staying up-to-date with emerging technologies.

🌐 Work Environment

Office Type: The company has a hybrid work environment, with offices in South San Francisco, California, United States, and Toronto, Ontario, Canada. The work environment is collaborative and innovative, with a focus on leveraging real patient biology and AI to accelerate drug discovery.

Office Location(s): South San Francisco, California, United States, and Toronto, Ontario, Canada.

Workspace Context:

Collaborative Workspace: The work environment is designed to foster cross-functional collaboration, with open-plan offices and dedicated spaces for team meetings and brainstorming sessions.
Development Tools: The team uses a range of development tools, including Python, Docker, AWS, Metaflow, Snakemake, and RunAI.
Testing Devices: The team has access to a range of testing devices, including GPUs and high-performance computing clusters.

Work Schedule: The work schedule is flexible, with a focus on delivering results and ensuring project deadlines are met. The team has regular check-ins to ensure everyone is on track and to address any blockers or challenges.

📝 Enhancement Note: The work environment is collaborative and innovative, with a focus on leveraging real patient biology and AI to accelerate drug discovery. The work schedule is flexible, with a focus on delivering results and ensuring project deadlines are met.

📄 Application & Technical Interview Process

Interview Process:

Phone Screen: A brief phone screen to assess technical fit and cultural alignment.
Technical Challenge: A take-home technical challenge to assess problem-solving skills and coding ability.
On-Site Interview: An on-site interview to assess technical depth, architecture design, and cultural fit.
Final Decision: A final decision based on the results of the technical challenge and on-site interview.

Portfolio Review Tips:

Cloud Infrastructure Projects: Highlight your experience in maintaining and scaling cloud-based data pipelines, with a focus on AWS, GCP, or Azure.
Data Pipeline Projects: Demonstrate your ability to design, develop, and maintain scalable software systems for high-throughput biological data analysis.
Collaborative Projects: Highlight your experience working with various teams to optimize workflows and ensure data quality and integrity.

Technical Challenge Preparation:

Cloud Infrastructure: Brush up on your knowledge of cloud infrastructure, including AWS, GCP, or Azure, and ensure you are familiar with containerization and pipeline orchestration tools.
Data Pipelines: Review your knowledge of data pipelines, including big data environments and scalable system design.
Problem-Solving: Practice problem-solving techniques and ensure you are comfortable with coding and debugging exercises.

ATS Keywords: [List of relevant web development and server administration keywords, organized by category: programming languages, cloud services, containerization, pipeline orchestration, big data environments, scalable system design, etc.]

📝 Enhancement Note: The interview process is designed to assess technical fit and cultural alignment, with a focus on cloud infrastructure, data pipelines, and scalable software systems. The technical challenge is designed to assess problem-solving skills and coding ability.

🛠 Technology Stack & Web Infrastructure

Cloud Services: AWS (preferred), GCP, or Azure

Containerization: Docker

Pipeline Orchestration: Metaflow, Snakemake

Big Data Environments: Hadoop, Spark, Hive

Scalable System Design: Microservices, Serverless Architecture

Infrastructure Tools: Terraform, Ansible

📝 Enhancement Note: The technology stack is designed to support cloud-based data pipelines and machine learning workflows, with a focus on scalability and performance.

👥 Team Culture & Values

Web Development Values:

Collaboration: The team values collaboration and cross-functional collaboration, with a focus on leveraging real patient biology and AI to accelerate drug discovery.
Innovation: The team values innovation and encourages experimentation and risk-taking to drive advancements in drug discovery.
Quality: The team values quality and ensures that data pipelines and software systems are reliable, scalable, and performant.
Continuous Learning: The team values continuous learning and encourages team members to stay up-to-date with emerging technologies and best practices.

Collaboration Style:

Cross-Functional Integration: The team encourages cross-functional collaboration between developers, designers, and stakeholders to ensure that data pipelines and software systems meet the needs of the business.
Code Review Culture: The team follows a code review process to ensure code quality, with a focus on readability, maintainability, and performance.
Knowledge Sharing: The team encourages knowledge sharing and provides regular training and development opportunities to ensure that team members stay up-to-date with emerging technologies and best practices.

📝 Enhancement Note: The team culture is collaborative and innovative, with a focus on leveraging real patient biology and AI to accelerate drug discovery. The team values collaboration, innovation, quality, and continuous learning.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Cloud Infrastructure Scalability: Ensure that cloud-based data pipelines can scale to meet the demands of the business, with a focus on performance and reliability.
Data Pipeline Optimization: Optimize data pipelines to ensure that they are efficient, reliable, and scalable, with a focus on minimizing data loss and maximizing throughput.
Big Data Environments: Ensure that big data environments are designed and implemented to support high-throughput biological data analysis, with a focus on scalability and performance.
Emerging Technologies: Stay up-to-date with emerging technologies in cloud infrastructure, data pipelines, and scalable software systems, and incorporate them into the company's technology stack.

Learning & Development Opportunities:

Technical Skill Development: The role offers the opportunity to develop and enhance technical skills in cloud infrastructure, data pipelines, and scalable software systems.
Conference Attendance: The company encourages conference attendance and provides funding for team members to attend relevant conferences and events.
Technical Mentorship: The role offers the opportunity to receive technical mentorship from senior team members and to provide mentorship to junior team members.

📝 Enhancement Note: The role offers significant technical challenges and learning opportunities, with a focus on cloud infrastructure, data pipelines, and scalable software systems. The role also offers the opportunity to stay up-to-date with emerging technologies and to provide and receive technical mentorship.

💡 Interview Preparation

Technical Questions:

Cloud Infrastructure: Be prepared to discuss your experience with cloud infrastructure, including AWS, GCP, or Azure, and your knowledge of containerization and pipeline orchestration tools.
Data Pipelines: Be prepared to discuss your experience with data pipelines, including big data environments and scalable system design.
Problem-Solving: Be prepared to discuss your problem-solving techniques and your ability to code and debug exercises.

Company & Culture Questions:

Company Mission: Be prepared to discuss the company's mission and how your role contributes to it.
Team Dynamics: Be prepared to discuss the team's dynamics and how you would contribute to a collaborative and innovative work environment.
Work-Life Balance: Be prepared to discuss your approach to work-life balance and how you would ensure that you are able to meet project deadlines while maintaining a healthy work-life balance.

Portfolio Presentation Strategy:

Cloud Infrastructure Projects: Highlight your experience in maintaining and scaling cloud-based data pipelines, with a focus on AWS, GCP, or Azure.
Data Pipeline Projects: Demonstrate your ability to design, develop, and maintain scalable software systems for high-throughput biological data analysis.
Collaborative Projects: Highlight your experience working with various teams to optimize workflows and ensure data quality and integrity.

📝 Enhancement Note: The interview process is designed to assess technical fit and cultural alignment, with a focus on cloud infrastructure, data pipelines, and scalable software systems. The technical challenge is designed to assess problem-solving skills and coding ability.

📌 Application Steps

To apply for this Senior Software Engineer (Biotech Cloud Infrastructure) position:

Submit Your Application: Submit your application through the application link provided.
Customize Your Portfolio: Customize your portfolio to highlight your experience with cloud infrastructure, data pipelines, and scalable software systems, with a focus on AWS, GCP, or Azure.
Optimize Your Resume: Optimize your resume for web technology roles, with a focus on project highlighting and technical skills emphasis.
Prepare for Technical Interview: Prepare for the technical interview by reviewing your knowledge of cloud infrastructure, data pipelines, and scalable software systems, and by practicing problem-solving techniques and coding exercises.
Research the Company: Research the company's mission, team dynamics, and work-life balance policies to ensure that you are a good fit for the role and the company culture.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Senior Software Engineer (Biotech Cloud Infrastructure)