Backend Engineer (Python / Golang)

About the Client

Our client is a US-based SaaS cybersecurity company building a platform that helps enterprise customers reduce risk, detect threats, and prevent breaches across the applications where modern businesses operate.

This is an opportunity to join the founding engineering team, work on customer-critical systems at scale, and help shape the technical standards, engineering culture, and long-term growth of a new R&D organization in Vietnam.

About the Role

We are looking for a Senior Software Engineer - Data Systems to join the founding R&D team in Ho Chi Minh City.

You will work on large-scale distributed backend systems, graph-based data models, and high-throughput data pipelines that power SaaS security and Agentic AI platforms.

What You Will Do

• 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.

What We Are Looking For

• 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.
• Strong proficiency in English communication.

Nice to Have

• Experience building cybersecurity products.
• Background in graph-based analytics, knowledge graphs, or relationship-driven risk modeling.
• Exposure to query engines, query optimization, or traversal and query layers.
• Experience with observability or real-time stream processing tools such as Grafana, Prometheus, OpenTelemetry, Flink, or Spark Streaming.
• Contributions to open-source distributed systems or graph-related projects.

AI-Native Engineering Expectations

As part of an AI-forward engineering environment, senior engineers are expected to use AI tools thoughtfully and contribute to AI-ready systems.

You should be comfortable with:

• Using AI-powered developer tools and critically evaluating AI-generated outputs.
• Core AI/ML concepts such as LLMs, embeddings, vector databases, retrieval, inference, and evaluation.
• Building AI-ready data infrastructure such as knowledge graphs, RAG pipelines, feature stores, or vector indexes.
• Supporting reliability, observability, and performance in AI-driven systems.

Why You'll Enjoy Working With This Team

• 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.

Working Model

This role is based in Ho Chi Minh City and is expected to be primarily in-office during the founding stage (at least 3 days per week). Working closely together will help the early team collaborate effectively, build technical trust, and establish a strong engineering culture as the R&D hub grows.

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