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GRADION
GRADION
201 – 500 Employees
ConsultingLogisticsTravel
GRADION is a digital and deep-tech consultancy that partners with businesses on technology strategy and delivery. Its work spans AI strategy and implementation, AI/ML development, technology advisory, cloud and DevOps engineering, cybersecurity, and technical audits. As part of NFQ Group, GRADION builds and operates platforms and provides engineering teams for clients in eCommerce, fintech, travel, manufacturing, and startups. Its global teams work across Asia, Europe, and MENA, with round-the-clock coverage and ISO 27001 processes. The company also offers leadership and AI-readiness training.
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Senior Software Engineer, AI Adoption

Principal-level engineer guiding AI adoption across Gradion’s digital platforms and Deep Tech solutions. Combines hands-on LLM development with architecture, reliability, and technical leadership, without direct reports.

VNVietnamHybridFull-timeSeniorEnglish RequiredAI EngineerMachine Learning Engineer
AWSCyber SecurityDistributed SystemsDockerGoGoogle Cloud PlatformJavaJavaScriptKubernetesNode.jsPython

Description

  • Set architecture and design direction for the most complex systems.
  • Build, prototype, and debug solutions alongside engineering teams.
  • Review high-risk implementations and strengthen engineering standards.
  • Work with Tech Leads to improve scalability, performance, and reliability, and address technical debt.
  • Evaluate and test new technologies, then document decisions.
  • Turn ambiguous client and stakeholder problems into clear technical direction.
  • Develop and work directly with LLMs, AI APIs, agents, RAG, and evaluation methods.
  • Find valuable AI use cases, implement them, and share lessons for reuse.
  • Guide architecture, system design, scalability, performance, reliability, technical debt, and technology choices across teams and projects.
  • Mentor engineers and shape technical decisions without direct reports.

Requirements

  • At least 8 years of experience building and operating production software.
  • Strong system design and architecture skills spanning scalability, performance, distributed systems, and reliability.
  • Deep expertise in at least one programming language and working familiarity with several others.
  • Ability to quickly understand an unfamiliar codebase.
  • Experience with technologies such as Python, Go, Node.js, Java, AWS or GCP, and Docker or Kubernetes; these are examples, not strict requirements.
  • Practical experience building LLM-based systems.
  • Experience with AI APIs and prompt and context design, plus at least one of agents, RAG, or evaluation.
  • Regular use of AI coding agents such as Claude Code or Codex for real work.
  • Evidence of setting technical direction across multiple teams or a large, long-running program.
  • Ability to mentor senior engineers and influence without formal authority.
  • Sound judgment about when not to build, when to reduce technical debt, and when to decline work.
  • Comfort working directly with clients and non-technical stakeholders.
  • Commitment to keeping up with developments in the field.
  • Bonus: experience operating AI systems at scale in production, including evaluation harnesses, guardrails, and cost and latency optimization.
  • Bonus: deep experience in data platforms, cybersecurity, robotics, or enterprise systems.
  • Bonus: experience building internal tools or platforms.
  • Bonus: open-source contributions, conference presentations, or technical writing.

Benefits

  • Performance bonus of up to two months’ pay.
  • Performance reviews twice a year.
  • Premium healthcare coverage.
  • 15 days of annual leave.
  • Full salary during the probation period.
  • Hybrid work arrangement.
  • Participation in technology communities.
  • Opportunities to work on global projects.
  • Ongoing learning opportunities.
  • Attractive salary.
  • Benefits that reflect your impact.

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