Vị trí Software engineer - infrastructure tại Data Science Dojo

Tổng quan vị trí

Vị trí Software engineer - infrastructure tại Data Science Dojo, dựa trên tin tuyển dụng chính thức đang mở. Vai trò hỗ trợ bàn giao kỹ thuật đáng tin cậy trong nhóm và khu vực được nêu.

Trách nhiệm

• Thiết kế, triển khai và vận hành phần mềm, dữ liệu hoặc hệ thống hạ tầng sản xuất phù hợp với vai trò.
• Phối hợp với các nhóm kỹ thuật, sản phẩm và khách hàng trong quá trình lập kế hoạch, đánh giá và bàn giao.
• Xử lý sự cố, ghi chép quyết định và cải thiện độ tin cậy, bảo mật và chất lượng.

Yêu cầu

• Kinh nghiệm chuyên môn phù hợp về phần mềm, dữ liệu, AI, bảo mật hoặc hạ tầng.
• Kỹ năng lập trình, giải quyết vấn đề và giao tiếp tốt.
• Có khả năng cộng tác hiệu quả với các nhóm phân tán và đáp ứng yêu cầu khu vực được nêu.

Công nghệ trong công việc

• C: As we grow, we need a Software Engineer – Infrastructure to automate, secure, and optimize the .
• LLM: Ejento AI, built by Data Science Dojo, is raising the bar for retrieval-augmented LLM applications, but innovation means nothing without resilient, scalable .
• RAG: Join us to turn infrastructure into a force multiplier for RAG-powered .
• CAN: While most teams patch together cloud scripts and call it DevOps, we’re building the backbone for AI applications that can’t afford to .

Hướng dẫn đánh giá mức độ phù hợp (tiếng Anh)

Phân tích dựa trên yêu cầu và trách nhiệm trong tin tuyển dụng của nhà tuyển dụng.

Understanding the scope. This Software engineer - infrastructure position at Data Science Dojo is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “While most teams patch together cloud scripts and call it DevOps, we’re building the backbone for AI applications that can’t afford to fail. Join us to turn infrastructure into a force multiplier for RAG-powered…” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the platform and infrastructure area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.

What the responsibilities signal. The posting specifically names “The posting does not list detailed responsibilities; confirm the team’s priorities with the employer.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved from the initial need to implementation, review, release or operational follow-through, where those stages apply. If the work involved other teams or users, distinguish your decisions from the group’s contribution. Avoid presenting a technology keyword as proof by itself: connect it to the problem you solved, the scale or complexity involved, and what changed after your work. The source may contain additional duties; review it directly before preparing your application.

How to read the requirements. The listed qualifications include “Relevant professional experience in software, data, AI, security or infrastructure engineering.”; “Strong programming, problem-solving and communication skills.”; “Ability to work effectively with distributed teams and the stated regional requirements.”. Mark each requirement as demonstrated, adjacent experience or a genuine gap, then use a concise example for the first two categories. A strong example explains what you personally owned, how you made trade-offs, how you validated the result and what you learned. If the posting specifies years of experience, language ability, certifications, location or eligibility, address those facts plainly in your CV or application rather than relying on the employer to infer them. Do not claim a qualification from exposure alone. For a requirement you do not meet, describe relevant transferable experience accurately and ask the recruiter whether it is mandatory.

Technology and working evidence. The technology terms associated with this listing are C: As we grow, we need a Software Engineer – Infrastructure to automate, secure, and optimize the ., LLM: Ejento AI, built by Data Science Dojo, is raising the bar for retrieval-augmented LLM applications, but innovation means nothing without resilient, scalable ., RAG: Join us to turn infrastructure into a force multiplier for RAG-powered ., CAN: While most teams patch together cloud scripts and call it DevOps, we’re building the backbone for AI applications that can’t afford to .. Treat this as a set of posting-derived signals, not a guarantee that every tool is used daily or that the list is complete. For each term relevant to your experience, prepare one concrete example: the system or workflow, the part you owned, the alternatives considered.

Phúc lợi

• Xem tin chính thức để biết phúc lợi và điều kiện việc làm hiện hành.

Về Data Science Dojo

Data Science Dojo provides education and professional training in data science, machine learning, analytics and AI. Its programs include bootcamps, online courses, workshops and corporate learning designed around practical skills and applied projects rather than theory alone.

The organization also publishes technical learning resources and serves both individual learners and enterprise teams. Roles can support instruction, curriculum, software platforms, data products or customer programs. Candidates should check whether the vacancy is a full-time employee, contract mentor or instructor position and confirm the expected teaching, delivery schedule and learner audience in the original posting.

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