ARYAN SOLUTIONS PTE. LTD. Hiring! Full Time AI Security Developer in Islandwide (Singapore), Earn up to SGD 10,000 - Ricebowl

Responsibilities:

 Experience - upto 5 years

• Integrate vendor AI security solutions with the firm’s enterprise infrastructure, platforms, APIs, identity systems, and deployment pipelines.
• Deploy, configure, and support LLM inference frameworks on Microsoft Azure or other cloud environment, ensuring scalability, reliability, security, and operational readiness.
• Develop Python-based services, APIs, automation scripts, integration components, and tooling to support AI security and LLM platform capabilities.
• Build solutions that enhance the firm’s security posture across LLM applications, AI agents, developer workflows, and enterprise AI infrastructure.
• Collaborate with security, infrastructure, platform engineering, cloud, and application development teams to deliver secure and production-ready AI capabilities.
• Work closely with teammates to design technical solutions, review implementation approaches, troubleshoot issues, and support delivery milestones.

Technical Skills Required

• Strong programming skills in Python.
• Hands-on experience developing AI agents or LLM-powered applications.
• Familiarity with agent development frameworks such as:
• OpenAI Agents SDK
• Google Agent Development Kit
• LangGraph
• Similar agent orchestration frameworks
• Familiarity with AI coding assistants such as Claude Code, GitHub Copilot, or equivalent tools.
• Understanding of core LLM concepts, AI agent concepts, and agentic workflow patterns.
• Basic understanding of Agentic AI security, LLM security, and common AI security risks.
• Familiarity with OWASP AI / LLM threats, including prompt injection, sensitive information disclosure, insecure plugin or tool use, excessive agency, and model misuse.
• Familiarity with the concepts of AI gateways and MCP gateways.
• Experience with OpenTelemetry or similar logging, tracing, and observability tools.
• Good knowledge of Linux, shell scripting, Git, Docker, and Kubernetes.
• Experience working with APIs, microservices, CI/CD pipelines, and cloud or containerized environments.
• Ability to work with security, infrastructure, and application teams to deliver secure enterprise AI capabilities.