Senior Software Engineer – AI Copilot

Zendesk

. Own and deliver end-to-end product features from technical design through implementation, testing, release, and iteration .

Posted 11/9/2026full-timeRemote • PortugalSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating large-scale, Internet-facing applications with a strong focus on Ruby and Python. Proven ability to integrate ML capabilities, mentor junior engineers, and deliver high-quality features through collaboration with cross-functional teams.

Highest-signal resume keywords

Ruby ProgrammingDistributed SystemsAWS Cloud InfrastructureDocker and KubernetesEnd-to-End Feature Ownership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingRESTful APIsCI/CD PracticesSQLData InfrastructureLLM Integration PatternsMetaflowEvent-Driven ArchitecturesA/B TestingFeature Flags

Soft Skills

Collaboration SkillsMentoring

Tools & Technologies

DockerKubernetesAWSSnowflakeDbtKafka

Industry Keywords

Machine LearningTechnical DesignSystem ReliabilityTechnical DebtProduct Management

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerKafkaKubernetesPythonRubySnowflakeSQL

About the role

Key responsibilities & impact

Own and deliver end-to-end product features from technical design through implementation, testing, release, and iteration
Work with ML Scientists and ML Engineers to integrate ML-powered capabilities into reliable, user-facing features
Contribute to technical design discussions and architecture decisions
Build and maintain scalable backend services, APIs, and integrations supporting AI-powered product experiences
Collaborate with Product Management, Design, and engineering teams to translate product requirements into technical work
Improve system reliability, performance, and maintainability
Identify and address technical debt
Mentor junior engineers through code review, pairing, and knowledge sharing

Requirements

What you’ll need

5+ years of experience building and operating large-scale, Internet-facing applications
Fluent in Ruby
Working proficiency in Python is a plus
Solid experience with distributed systems, RESTful APIs, and AWS cloud infrastructure
Experience with Docker, Kubernetes, and CI/CD practices
Track record of owning features end-to-end and delivering them to production with high quality
Ability to work with uncertainty and changing priorities
Ability to collaborate with ML engineers and scientists
Strong collaboration skills
Preferred: Experience with SQL and data infrastructure, including Snowflake and dbt
Preferred: Exposure to LLM integration patterns, including prompt engineering, evaluation, monitoring, or multi-provider setups
Preferred: Familiarity with ML pipeline tooling such as Metaflow or ML frameworks
Preferred: Experience with event-driven architectures such as Kafka
Preferred: Experience with A/B testing, feature flags, and incremental rollouts

Benefits

Comp & perks

Hybrid way of working with flexibility to work remotely for part of the week
Inclusive workplace experience
Reasonable accommodations for applicants with disabilities and disabled veterans