Full Stack Engineer (AI Platforms & Enterprise Applications)

About the Role

We are looking for a Full Stack Engineer to help build and enhance enterprise AI services utilized across large-scale organizations.

You will be part of a team supporting enterprise AI platforms, including ChatGPT Enterprise, Microsoft 365 Copilot, Gemini Enterprise, and emerging AI-enabled applications and services.

This role focuses on the hands-on development and implementation of applications, APIs, integrations, and automation solutions. You will be responsible for delivering assigned engineering tasks independently, troubleshooting technical issues, and contributing to production support under the guidance of senior engineering leadership.

Candidates with strong full-stack engineering experience and a willingness to learn are encouraged to apply. Experience with enterprise AI platforms or agentic AI is advantageous but not mandatory.

What You'll Be Doing

Full Stack Application Development

• Design, develop, test, deploy, and maintain secure and scalable web applications, backend services, APIs, and databases.
• Take ownership of solutions from development through production support.

Enterprise Systems Integration

• Build and maintain APIs and connectors integrating AI platforms with identity services, enterprise applications, document repositories, and existing systems.

AI Enablement & Workflow Automation

• Develop automation for user provisioning, licence management, and operational workflows.
• Support AI-powered applications, Model Context Protocol (MCP) integrations, and agentic workflows with appropriate security and approval controls.

Cloud & DevOps Engineering

• Implement and maintain CI/CD pipelines, automated testing, application monitoring, and deployment processes.
• Troubleshoot production issues, optimize performance, and improve application reliability.

Security & Compliance

• Apply secure coding practices.
• Implement authentication, authorization, access controls, data protection, and audit logging.
• Support security assessments, vulnerability remediation, and compliance with applicable security requirements.

Engineering Collaboration & Continuous Improvement

• Collaborate with product managers, engineers, cybersecurity teams, and stakeholders to translate requirements into practical solutions.
• Participate in code reviews, technical documentation, and continuous improvement initiatives, including the responsible use of AI-assisted development tools.

Requirements

Education

• Degree or diploma in Computer Science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience.

Experience

• Relevant hands-on experience in full-stack software development, including building, deploying, and maintaining applications in production environments.
• Proven experience delivering working software and demonstrating practical engineering capabilities.
• Experience with enterprise AI platforms is advantageous but not required.

Essential Requirements

Programming & Development

• Strong programming skills in at least one of the following: TypeScript, JavaScript, Python, Java, or C#.
• Hands-on experience with frontend frameworks such as React, Angular, or Vue.js, and backend application development.
• Experience developing REST APIs and working with relational or NoSQL databases.

Software Engineering Practices

• Familiarity with Git, software testing, CI/CD, and modern development practices.
• Understanding of application security, authentication, authorization, and secure data handling.
• Ability to troubleshoot application issues and support software through deployment and production operations.

Preferred Requirements

Cloud & Infrastructure

• Experience with Microsoft Azure, AWS, or Google Cloud, including containers or Infrastructure as Code (IaC).

Enterprise Integration

• Experience integrating enterprise applications, including Microsoft Graph APIs, Microsoft Entra ID, or workflow automation systems.

AI & Emerging Technologies

• Exposure to Generative AI, LLM APIs, tool calling, AI agents, Retrieval-Augmented Generation (RAG), or Model Context Protocol (MCP).
• Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, or Cursor.

Monitoring & Performance

• Familiarity with application monitoring, observability, and performance optimization.

Industry Exposure

• Experience developing applications in enterprise, regulated, or government environments.

What Makes You Successful

Problem Solving & Ownership

• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to take ownership of engineering deliverables from development through production support.

Communication & Collaboration

• Good written and verbal communication skills, with the ability to explain technical solutions to different stakeholders.
• Ability to work independently and collaborate effectively with multidisciplinary teams.

Learning & Adaptability

• Adaptability and willingness to learn.
• Strong interest in emerging AI technologies.

Quality & Engineering Excellence

• Commitment to software quality, security, reliability, and continuous improvement.