AI Engineering Lead

About Us

We're one of Asia's fastest-growing cyber resilience firms, moving from consultancy delivery to a platform-led managed-services model. Our AI initiatives turn the repetitive parts of a penetration test and related processes into an agentic workflow. We are seeking a Senior AI Engineering to help build and advise our AI Initiatives to enhance how cybersecurity services are delivered, managed, and scaled.

The Opportunity

This is not a traditional software engineering role.

You will work directly with senior leadership to help design and build AI-powered systems that improve operational efficiency, knowledge management, decision support, and customer experience.

This role is ideal for someone who enjoys solving complex real-world problems and wants to shape the future of AI adoption within a high-growth technology company.

Responsibilities

AI Platform Design and Development

• Design and build scalable AI-enabled applications and services.
• Develop agentic workflows and intelligent automation.
• Integrate large language models into business processes.
• Evaluate and select appropriate AI technologies.
• Collaborate with stakeholders to translate business requirements into technical solutions.

AI Operations & Governance

• Improve reliability, accuracy, and observability of AI systems.
• Establish evaluation and testing frameworks.
• Support security, compliance, and governance requirements.
• Design architectures that respect strict data privacy, governance, and residency requirements (e.g., handling sensitive enterprise logs, PII, and on-premise/private cloud LLM deployments).

Leadership

• This is a hands-on, "Player-Coach" role. In the first 6–12 months, your primary focus will be architecture, rapid prototyping, and help the engineering team to write production-ready code to establish our core AI capabilities. As these initiatives scale, you will take the lead in hiring, structuring, and mentoring a dedicated AI engineering squad
• Serve as a domain expert within the AI engineering function. Advise the CEO alongside R&D leaders on AI direction, vendor selection, budget, and hiring.
• Contribute to long-term technology strategy.
• Represent product’s engineering side to enterprise clients when they press on architecture, safety, or compliance. Most of our top-tier clients want to talk to the humans behind the AI.

Requirements

AI Engineering

Experience with some of the following:

• Familiarity with multi-agent architecture: orchestrator, specialist loops, tool registry, and inter-agent communication contracts. Experience with agentic frameworks (LangGraph, DSPy, PydanticAI, custom ReAct).
• Experienced with Prompt engineering (versioned prompts, hot-reload, evaluation-driven changes). Not one-off tweaks based on vibes.
• Understand the LLM client abstraction: provider routing, retry / fallback, tool-use API differences between Anthropic and OpenAI, and the local-model path (Ollama, vLLM). Able to make a platform model-agnostic in code, not just in marketing.
• Observability: CoT, AI explainability, traces, replayable engagements, per-run cost/quality dashboards.
• AI evaluation and testing.

Cloud & Infrastructure

Experience with one or more:

• Experience deploying applications in cloud environments (AWS, Azure, or GCP). You don't need to be a DevOps engineer, but you should be comfortable navigating cloud services and containerized environments (Docker).

Nice to Have

• Experience with local-model inference: Ollama, vLLM, llama.cpp, or bare-metal HuggingFace serving.
• Cyber security fundamental knowledge and AI security risks.
• You've shipped LLM-driven production systems.
• You've debugged an agent that went off-plan and you know why.
• You've built RAG pipelines, evaluation harnesses, prompt versioning, cost tracking.
• Knowledge / experience on event-driven architectures.
• Knowledge / experience on knowledge graph systems.

Why Join Us

• Opportunity to shape the company’s AI capabilities from an early stage.
• You'll be the AI systems lead of a shipped product with real users, not a research prototype.
• Exposure to real-world enterprise and cybersecurity challenges.
• Significant influence over technology decisions and future engineering direction.
• Opportunity to build solutions that create measurable business impact.

If you are excited by the intersection of AI, software engineering, and complex operational challenges, we would love to hear from you.

Application Requirements

• Resume.
• GitHub profile (if available).
• Portfolio of relevant projects.
• Brief description of the most impactful system you have designed or built.