Senior DevSecOps Engineer

12026-01-31
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We are scaling our custom-deployed AI chatbot solutions as the foundation for future agentic workflow projects and our Managed AI Services offering. While we are still early in this journey, we are actively delivering:

  • 3 client deployments currently in UAT

  • 2 additional deployments planned for early 2026

To support secure, repeatable, and production-grade scaling, we are seeking a Senior DevSecOps Engineer. This role will provide technical leadership, uplift engineering and security standards, and deliver practical, actionable guidance to our local development team.

Responsibilities

  • Act as a technical leader and advisor for AI/LLM-based client deployments, ensuring production-ready architecture and security.
  • Review and improve system architecture, deployment pipelines, and operational standards for AI chatbot platforms.
  • Lead DevSecOps best practices, including secure CI/CD pipelines, infrastructure automation, and runtime security.
  • Conduct security and architecture reviews, including threat modeling, risk identification, and mitigation strategies.
  • Translate high-level architectural and security recommendations into clear, actionable tasks for engineers.
  • Guide the team in designing scalable, repeatable deployment patterns for multiple client environments.
  • Collaborate closely with engineers and stakeholders, leading technical discussions and aligning solutions with business goals.
  • Support the long-term evolution toward agentic workflows and Managed AI Services.
  • Advise on best practices for Azure-based AI services, including Azure Machine Learning and Azure AI Foundry, where appropriate.

Requirements

  • Excellent spoken and written English, with the ability to lead technical discussions with engineers and non-technical stakeholders.
  • Proven experience deploying AI/LLM applications to production, with a strong focus on security, reliability, and scalability (not research-only).

Strong DevSecOps expertise, including:

  • Docker and containerization
  • Kubernetes (preferred)
  • CI/CD pipeline design and implementation
  • Infrastructure as Code (Terraform preferred)
  • Secrets management
  • Monitoring and observability
  • AI & Cloud Platform Experience

Hands-on experience with Azure Machine Learning, including:

  • Model deployment and endpoint management
  • Environment and dependency management
  • Secure access to models and data
  • Familiarity with Azure AI Foundry (Azure AI Studio / Azure AI services), including:
  • LLM orchestration and prompt management
  • Integration with Azure OpenAI or other model providers
  • Security, governance, and access controls for AI services
  • Experience designing multi-tenant or client-isolated AI deployments is a strong plus.

Demonstrated ability to:

  • Review system architecture and security posture
  • Perform threat modeling for AI systems (LLMs, APIs, data flows, model access)
  • Convert recommendations into practical implementation plans for engineering teams

What we offer

  • Attractive and competitive performance-based compensation package
  • Generous year-end 13th-month bonus
  • Loyalty and annual dedication rewards
  • Full gross salary paid during probation
  • 12 annual leave days, 11 public holidays, 1 Christmas day off and 5 sick leave days
  • Flexible check-in time, 1-day remote work per week, and the freedom to work from any of our offices in Da Nang, Hue, or Ha Noi
  • Comprehensive healthcare package and annual health check-ups
  • Team-building allowance, Annual company trips, and Gathering Party every Thursday for a fun and connected workplace
  • Sports & hobby clubs with football, badminton, biking, running, chess, or music band groups
  • Continuous learning & development with exclusive technical & soft skills training, English classes, and technical clubs
  • Financial aid for marriage, newborns, and bereavement to support you through every stage of life

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