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インターンシップ 在宅勤務

AI & Cloud Engineering Internship (Remote) at SYplat

SYplat

Remote ・フルタイムインターンシップ

最初に応募しよう

手当
Stipend: INR 15,000 – INR 15,000 / month
間隔
6ヶ月
始める
すぐに
求人情報
5
応募資格者

Open to final-year students and graduates in Computer Science Engineering or related technology programs who are available for full-time remote internship starting between July 9 and August 13, 2026, for a six-month tenure. Women looking to start or restart their careers are encouraged to apply. Ca…

作業モード
在宅勤務
教育
Computer Science Engineering or related
再開する
応募必須

インターンシップについて

Internship Overview

Join SYplat as an AI & Cloud Engineering intern working from home. This role involves contributing to the creation of AI-driven security and compliance software by developing systems and workflows that integrate AI subsystems, agents, and enterprise policies. Interns will engage in designing explainable, traceable AI solutions for identity and access management while supporting cloud integration on platforms like Microsoft Azure and SAP BTP.

Key Responsibilities

  • Design AI subsystems and workflows to meet enterprise requirements.
  • Develop systems interpreting policies, operational signals, and context to automate workflows.
  • Implement AI use cases for identity lifecycle, access control, audits, and policy management.
  • Leverage retrieval-augmented and knowledge-driven methodologies aligned with platform goals.
  • Establish continuous evaluation loops ensuring AI quality, explainability, and safety.
  • Utilize AI-assisted coding, testing, and documentation tools to enhance development.
  • Conduct AI-driven requirement analysis and system design.
  • Create reusable templates, test patterns, and checklists to support engineering efforts.
  • Ensure responsible AI use through validation and review processes.
  • Develop enterprise agent systems enabling governed, auditable actions.
  • Build workflows coordinating identity, security, and compliance agents with human-in-the-loop approvals.
  • Integrate APIs, knowledge graphs, and workflow engines for smooth agent cooperation.
  • Implement cloud services, APIs, data pipelines, storage, and messaging using Azure and SAP BTP.
  • Apply observability, access patterns, logging, metrics, and secure secrets management.
  • Create rapid prototypes advancing toward production standards.
  • Incorporate robust validation, error handling, retries, idempotency, and testing techniques.
  • Maintain operational documentation, logs, and deployment processes for safe releases.
  • Work within Agile frameworks including standups, sprint planning, demos, reviews, and retrospectives.
  • Collaborate effectively with architects and interdisciplinary teams to ensure delivery.

Eligibility Criteria

  • Candidates must be available for a remote internship starting between July 9, 2026, and August 13, 2026, lasting 6 months.
  • Open to final-year students or graduates in Computer Science Engineering or related fields.
  • Applicants should demonstrate strong curiosity, learning aptitude, discipline, ownership, problem-solving, and analytical skills.
  • Women seeking to start or restart their careers are encouraged to apply.
  • This full-time hybrid internship initially remote with potential in-office work, with fully remote options for exceptional candidates.

Compensation and Benefits

  • A monthly stipend of ₹15,000 is provided during the internship.
  • Interns receive a certificate upon completion and may be offered a job opportunity.
  • The working schedule comprises five days a week.
  • Opportunity for conversion to a permanent role with an expected annual salary of ₹300,000 upon successful performance.

About SYplat

SYplat is an AI-centric security and compliance software startup headquartered in Delaware, USA. Their platform unifies identity lifecycle, access management, risk auditing, and data protection into a semantic security fabric, enabling rapid, confident enterprise operations. AI agents embedded in the platform interpret policies, verify evidence, mitigate risks, and coordinate actions with complete traceability and explainability.

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