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Trulioo

Senior Software Engineer – Back-end, Server

Trulioo

. Lead the architecture and development of high-throughput, low-latency back-end services for Trulioo’s Document and Biometric Verification platform .

Posted 9/16/2026full-timeVancouver • CanadaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing high-throughput, low-latency back-end services, with a strong focus on microservices architecture, distributed systems, and real-time identity verification. Proficient in Kotlin and modern JVM concurrency, with hands-on experience in deploying AI/ML models and optimizing performance across cloud environments.

Highest-signal resume keywords
Kotlin ProficiencyMicroservices ArchitectureApache Kafka ExperienceGRPC/Protobuf API DesignDistributed NoSQL Database Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Back-End Software EngineeringEvent-Driven MicroservicesKotlin CoroutinesService-Oriented ArchitectureAsynchronous MessagingAPI VersioningData Access OptimizationMulti-Step Verification WorkflowsAI/ML Code AssessmentCloud Environment Operations
Soft Skills
Mentoring EngineersCollaboration with Teams
Tools & Technologies
KubernetesAI Coding AssistantsContainerizationService MeshesInfrastructure-as-Code
Industry Keywords
Identity VerificationDocument VerificationReal-Time ProcessingLatency OptimizationScalable Systems

Tech Stack

Tools & technologies
ApacheCloudGRPCJavaKafkaKotlinKubernetesMicroservicesNoSQL

About the role

Key responsibilities & impact
  • Lead the architecture and development of high-throughput, low-latency back-end services for Trulioo’s Document and Biometric Verification platform
  • Design and operate distributed, event-driven microservices for real-time identity verification
  • Ingest captured documents and biometric data
  • Coordinate ML inference and third-party vendor calls
  • Return verification decisions at scale across multiple global regions
  • Bridge developer-facing APIs, asynchronous processing pipelines, and ML and infrastructure systems
  • Design, build, and maintain secure, modular, horizontally scalable microservices
  • Own gRPC/Protobuf contracts and REST/OpenAPI external client interfaces, including versioning and backward compatibility
  • Build Apache Kafka streaming pipelines with topics, consumers, and stream-processing topologies
  • Model and optimize data access across distributed NoSQL databases, search/indexing systems, and caching layers
  • Implement durable, multi-step verification workflows using a workflow engine
  • Drive sub-second end-to-end verification latency and predictable throughput
  • Tune coroutine concurrency, backpressure, and event-driven autoscaling
  • Drive technical architecture and mentor engineers
  • Collaborate with Machine Learning, Infrastructure, and Product teams
  • Deploy computer vision models and vendor integrations into production
  • Use AI coding assistants and internal tooling to accelerate design, implementation, testing, and code review
  • Apply AI/ML-driven analysis for anomaly detection, log and metrics insight, capacity forecasting, pipeline performance, throughput, and decision logic optimization

Requirements

What you’ll need
  • 8+ years of back-end/server software engineering experience delivering production-grade distributed services or platforms
  • Deep proficiency with Kotlin, or strong Java experience transitioning to Kotlin
  • Modern JVM concurrency, including Kotlin Coroutines and structured concurrency
  • Hands-on experience with service-oriented or microservice architectures
  • Experience with gRPC/Protobuf and/or REST, including API design, versioning, and inter-service communication patterns
  • Experience with event streaming and asynchronous messaging; Apache Kafka strongly preferred
  • Experience with consumer scaling, exactly-once/idempotent processing, and failure handling
  • Practical experience with distributed NoSQL databases, search/indexing systems, and caching strategies at scale
  • Experience operating services in a public cloud environment on Kubernetes
  • Familiarity with containerization, service meshes, and infrastructure-as-code
  • Expertise managing memory, thread/coroutine concurrency, connection pooling, and payload optimization
  • Daily hands-on use of AI coding assistants such as GitHub Copilot, Claude Code, or Cursor
  • Ability to critically assess AI-generated code and outputs for correctness, security, and performance
  • Working understanding of LLM and ML production behavior, including latency, cost, and failure modes

Benefits

Comp & perks
  • Health, dental, and vision coverage
  • Retirement plans with company match
  • Paid time off
  • Parental leave
  • Annual education & training stipend equivalent to $1,000 in local currency
  • Flexible hybrid working environment
  • Weekly lunches
  • Quality coffee
  • Regular social events
  • Parent rooms at many locations
  • On-site gyms at many locations
  • Comfortable lounges
  • Adaptable workstations
  • Wellness workshops and events
  • Complimentary Headspace subscription
  • Employee Resource Groups and inclusive community programs