Senior Backend Engineer – Python, Golang

qode.world

. Design and build large-scale distributed backend systems and graph-based data models .

Posted 10/3/2026full-timeHo Chi Minh City • VietnamSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in designing and building large-scale distributed backend systems, with strong proficiency in Python and Go. Capable of developing high-throughput data ingestion pipelines and contributing to AI-ready infrastructure while ensuring secure coding practices and compliance with information security policies.

Highest-signal resume keywords

Python ProficiencyGo ProficiencyDistributed Systems DesignGraph Database ExperienceAPI Design for High-Traffic Workloads

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Applicant Tracking System Keywords

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Hard Skills

Backend Systems DevelopmentData Ingestion PipelinesGraph Data ModelingSecure Coding PracticesAPI DesignData Storage SystemsStreaming SystemsAI/ML ConceptsReliability EngineeringObservability

Soft Skills

Strong Communication SkillsCollaboration

Tools & Technologies

DockerKubernetesAWSGCPPostgreSQLNoSQL DatabasesS3KafkaRedisAI-Powered Developer Tools

Industry Keywords

Distributed SystemsData ProcessingInformation SecurityTechnical DocumentationRemote Work Compliance

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerGoogle Cloud PlatformKafkaKubernetesNeo4jNoSQLPostgresPythonRedisGo

About the role

Key responsibilities & impact

Design and build large-scale distributed backend systems and graph-based data models
Develop high-throughput, low-latency data ingestion and processing pipelines using Python and Go
Own significant features end-to-end, from technical design to production rollout
Partner with product and security research teams to deliver new capabilities at scale
Identify production risks and build observable, resilient solutions before they become customer-impacting issues
Collaborate with engineers through design reviews, code reviews, and technical discussions
Contribute to an AI-forward engineering environment and AI-ready systems
Use AI tools thoughtfully and contribute to AI-ready infrastructure and reliability

Requirements

What you’ll need

7+ years of software engineering experience, with significant experience in backend systems
Strong proficiency in Python and/or Go
Hands-on experience designing, building, and operating distributed systems in production, including replication, partitioning, backpressure, and idempotency
Experience with graph data and graph databases such as Neo4j, JanusGraph, Neptune, TigerGraph, or similar tools
Strong understanding of storage and streaming systems, including PostgreSQL, NoSQL databases, S3, Kafka, and Redis
Experience designing APIs and backend services for high-traffic, multi-tenant workloads
Familiarity with Docker, Kubernetes, and cloud platforms such as AWS or GCP
Strong communication skills, including the ability to contribute to design discussions and write clear technical documents
Solid understanding and application of secure coding practices, including secrets management, access control, and handling of sensitive data throughout the software development lifecycle
Strong awareness of protecting source code, technical documentation, and customer data while complying with company information security policies in a remote working environment
Ability to collaborate with QA/IT/ISRM teams to remediate vulnerabilities, address information security risks, and support incident investigation when required
Strong proficiency in English communication
Comfortable using AI-powered developer tools and critically evaluating AI-generated outputs
Familiarity with core AI/ML concepts such as LLMs, embeddings, vector databases, retrieval, inference, and evaluation
Comfortable building AI-ready data infrastructure such as knowledge graphs, RAG pipelines, feature stores, or vector indexes
Able to support reliability, observability, and performance in AI-driven systems

Benefits

Comp & perks

Join the founding engineering team of a growing Vietnam R&D hub with strong long-term investment
Work on large-scale distributed systems, graph data platforms, and AI-driven security products used by enterprise customers globally
Own meaningful product features from design to production and contribute to engineering standards from an early stage
Collaborate closely with experienced global engineering and security research teams
Solve technically challenging problems with meaningful product impact
Primarily in-office working model with close team collaboration