Role Summary

The engineer will help design, build, and maintain AI agents supporting operations and decision-making within the organization — conversational agents, workflow automation, and decision-support tools. Working alongside senior colleagues, product owners, and domain experts, they will gather requirements, prototype, build, and help iterate on solutions after release. This is a junior role: the organization expects to mentor and grow the right person, so aptitude and a strong foundation matter more than years of experience.

The role begins remotely on a defined, real project. If it goes well, the organization intends to bring the engineer onsite in Abu Dhabi for an ongoing role — the initial engagement is both the work and the trial.

How We Work

The work is about building AI agents well — sound agent design, secure integration with APIs and data, and solutions that are maintainable and compliant — rather than any one platform. In practice much of it runs on the organization's Microsoft environment (Copilot Studio or Azure AI Foundry for a conversational front end, Azure for orchestration and infrastructure, and a domain-appropriate language such as Python, Rust, or Julia — or Foundry — for backend logic), spanning both low-code and pro-code. Experience on a comparable enterprise-grade cloud or automation stack is equally welcome, provided the candidate can meet the organization's security, data-residency, compliance, integration, and maintainability requirements and adapt to its environment. The role is not tied to a single specialization; a candidate comfortable across the stack, or eager to become so, is well suited to it, and willingness to learn matters more than mastery of any one tool at this level.

Key Responsibilities

Help gather and translate business requirements into technical designs and documentation.

Prototype and build AI agents (conversational, workflow-automation, and decision-support) on the organization's approved stack, with guidance from senior colleagues.

 Integrate agents with APIs, databases, and cloud services, and help monitor and iterate on deployed solutions.

Document work clearly so the internal team can operate and maintain it.

 Learn the organization's stack, standards, and domain, and grow into greater ownership over time.

Mandatory

·         A degree in a related field (e.g. Computer Science, AI, Software Engineering, or similar), or equivalent demonstrable ability.

·         A genuine grounding in building AI agents or LLM-based applications — through study, personal projects, internships, or early professional work. Production experience is not required at this level.

·         Working knowledge of LLMs, conversational AI, and basic agent design patterns.

·         Strength in at least one of two areas: pro-code (sound programming fundamentals in a relevant language, with comfort learning others) or low-code / workflow automation (building in a platform such as Power Platform, n8n, or similar). Either path qualifies; both is a plus.

·         An awareness of data security and privacy as something to design for, not bolt on.

·       Exposure to DevOps practices — an understanding of version control, CI/CD, and automated testing and why they matter.

·       Clear English and effective remote collaboration, working on Abu Dhabi time and meeting the eligibility conditions above.

·       A credible, evidenced background in relevant work. A portfolio or sharable projects are welcome but not required — where work can't be shared (e.g. defense or other sensitive settings), a clear account of it plus references is equally valid.

Beneficial

·         Strength across both paths — comfortable in pro-code and in low-code / workflow automation — able to move between backend logic, integration, and a conversational or automation front end.

·         Some exposure across the stack — a conversational front end (Copilot Studio / Azure AI Foundry), cloud infrastructure (Azure), and backend code (a domain language or Foundry).

·         Hands-on experience with Azure or the Power Platform.

·         Hands-on experience with DevOps — working with Git, writing tests, and building or running CI/CD pipelines.

·         Experience integrating applications with APIs, databases, or cloud services.

·         Awareness of LLM-specific risks such as prompt injection and data leakage, and how to guard against them.

·         A Master's degree, or relevant certifications in Azure, security, or AI.

·         Fluency with AI-assisted / agentic coding tools — Claude (incl. Claude Code) in particular, as the organization operates a Claude Enterprise environment.