Senior Backend Developer, AI Systems

Jobgether; United States; Remote; USD 102,000 - 143,000; Full time

Job summary

Jobgether is seeking a senior engineer to lead the architectural transformation of our core recommendation pipeline into a modern, distributed system. You will design, develop, deploy, and operate scalable backend services powering personalized content, send-time optimization, and frequency capping.

You will collaborate with machine learning engineers and product stakeholders to translate requirements into robust architectures, own critical components end-to-end, and champion best practices in

Qualifications

• 5+ years of professional software engineering experience, focused on distributed systems.
• Experience building highly available, fault-tolerant, high-concurrency distributed systems.
• Strong fundamentals: system design, testing, Git, code reviews, CI/CD.
• Strong Python backend development experience.
• Experience with Spark, Flink, or Beam; Spark preferred.
• Understanding of distributed systems concepts: consensus, partitioning, replication, back-pressure, idempotency, failure handling.
• Cloud experience with GCP, AWS, or Azure.
• Familiarity with microservices, Kubernetes, Kafka, gRPC.
• CI/CD and automated deployments.
• Docker, Kubernetes, and GitHub Actions familiarity.
• Leadership and communication to influence architectural decisions.
• Analytical, production problem-solving.
• Adaptability and lifelong learning.

Responsibilities

• Lead architectural transformation of the core recommendation pipeline into a modern distributed system.
• Design, develop, deploy, and operate scalable backend services for personalization.
• Identify and resolve performance bottlenecks and scalability issues across distributed systems.
• Collaborate with ML engineers and product teams to translate requirements into robust designs.
• Own end-to-end critical components, including architecture, development, deployment, and incident response.
• Promote best practices in testing, observability, and operational excellence.
• Contribute to continuous improvement of distributed infrastructure for high availability.
• Provide technical leadership and mentorship to peers.
• Participate in architectural discussions to influence AI infrastructure direction.
• Foster accountability and a culture of collaboration and lifelong learning.

Skills

Distributed systems

Python

Spark

Flink

Beam

Kubernetes

Kafka

gRPC

CI/CD

Unit testing

Git

Code reviews

Docker

GitHub Actions

Mentorship

Tools

Docker

GitHub Actions

CI/CD tooling

Job description

Accountabilities:

- Lead the architectural transformation of the core recommendation pipeline into a modern distributed system, delivering incremental improvements while maintaining production stability and reliability.

- Design, develop, deploy, and operate scalable, fault-tolerant backend services supporting large-scale personalization capabilities, including content selection, send-time optimization, subject line personalization, and frequency capping.

- Identify, investigate, and resolve performance bottlenecks, reliability issues, and scalability limitations across distributed systems.

- Collaborate with machine learning engineers and product stakeholders to translate business and technical requirements into robust architectural designs and production-ready solutions.

- Take end-to-end ownership of critical system components, overseeing architecture, development, implementation, deployment, monitoring, and incident response.

- Champion engineering best practices across system design, code quality, automated testing, observability, and operational excellence.

- Contribute to the continuous improvement of distributed infrastructure, ensuring high availability, fault tolerance, and efficient system performance.

- Provide technical leadership and mentorship to other engineers, encouraging knowledge sharing, sound architectural decisions, and strong engineering standards.

- Participate in architectural discussions and technical decision-making, helping shape the long-term direction of AI infrastructure and backend systems.

- Promote a culture of accountability, technical excellence, collaboration, and continuous learning.

Requirements:

- At least 5 years of professional software engineering experience, with a strong focus on distributed systems.

- Extensive experience designing, building, and operating large-scale distributed systems that are highly available, fault-tolerant, and capable of handling high concurrency.

- Strong software engineering fundamentals, including system design, unit testing, Git, code reviews, and continuous integration and delivery practices.

- Strong programming skills in Python and experience developing reliable, maintainable backend services.

- Experience with distributed data processing frameworks such as Apache Spark, Apache Flink, or Apache Beam. Hands-on experience with Apache Spark is considered an advantage.

- Solid understanding of distributed systems fundamentals, including consensus, partitioning, replication, back-pressure, idempotency, and failure handling.

- Practical experience with cloud infrastructure providers such as Google Cloud Platform (GCP), AWS, or Microsoft Azure.

- Familiarity with modern distributed systems and microservices technologies, particularly Kubernetes, Kafka, and gRPC.

- Experience with modern software development lifecycle practices, including automated testing, continuous integration, continuous delivery, and automated deployments.

- Familiarity with containerization and development tools such as Docker, Kubernetes, and GitHub Actions.

- Strong technical leadership and communication skills, with the ability to influence architectural decisions, collaborate across teams, and mentor fellow engineers.

- Excellent analytical and problem-solving abilities, particularly when diagnosing and resolving complex issues in production environments.

- Adaptability, curiosity, and a strong commitment to continuous learning and professional development.

Benefits:

- Competitive annual base salary ranging from CAD 143,000 to CAD 200,000 , depending on relevant experience, technical expertise, and qualifications.

- Potential additional bonus compensation, depending on the position and final offer.

- Comprehensive medical, financial, and additional employee benefits.

- Remote working opportunities within Canada.

- Opportunity to work on a high-impact AI-powered recommendation engine supporting billions of marketing decisions.

- Exposure to advanced distributed systems, machine learning infrastructure, and large-scale cloud technologies.

- Opportunity to influence architectural strategy and contribute to significant technical transformation initiatives.

- Collaborative environment with experienced engineers, machine learning specialists, and product professionals.

- Opportunities to develop technical leadership skills and mentor other engineers.

- Inclusive and diverse workplace culture that values different perspectives, backgrounds, and experiences.

- Encouragement to apply even if you do not meet every listed qualification, recognizing that transferable skills and diverse experiences bring valuable perspectives to the team.