Senior AI Engineer

Company not disclosed

Hong Kong, Hong Kong SAR
Salary not specified
Posted
Full-time
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Job Description

Looking to take your digital career to a whole new level? Then this role is for you! First Page is a certified “GREAT PLACE TO WORK” and is a global digital marketing firm that transforms the way companies do business online. Since 2011 our mission has been to create amazing digital experiences by implementing game-changing digital strategies. As APAC’s highest-rated digital agency, First Page has seen insane growth and won numerous awards over the past 3 years. The role As a Senior AI Engineer, you’ll design, build and maintain production-grade AI and automation systems across the business. This is a hands-on engineering role. You’ll take projects from requirements through to production, working closely with the AI Lead, junior engineers and internal stakeholders. You’ll write and review code, integrate external platforms, debug live issues and help establish strong engineering practices across the team. You’ll also play an important role in AI adoption. That means demonstrating what you build, documenting it clearly and helping non-technical teams use AI tools and workflows effectively. What you’ll do 1. Build production AI and automation systems - Design, build and maintain AI-powered features, integrations and workflow automations. - Turn business requirements into reliable technical solutions. - Build robust API and data pipelines with appropriate authentication, scheduling, validation and error handling. - Create idempotent workflows that can be safely retried and rerun. - Integrate CRMs, databases, marketing platforms and other third-party systems. - Develop LLM-based features using models and providers such as GPT, DeepSeek and OpenRouter. - Evaluate model outputs and balance quality, latency, reliability and cost. - Write clean, testable and maintainable Python. - Add appropriate tests, CI checks, logging, monitoring and operational documentation. - Debug production issues and improve systems based on real-world usage. 2. Contribute to architecture and technical quality - Work with the AI Lead to shape solution architecture and technical decisions. - Contribute to model-selection, build-vs-buy and system-design decisions. - Review pull requests and provide clear, constructive technical feedback. - Identify reliability, security, data-quality and maintainability risks before systems ship. - Help establish reusable patterns for integrations, LLM workflows and internal tools. - Prefer clear, dependable solutions over unnecessary complexity. - Improve existing systems—not just build new ones. 3. Support AI enablement and adoption - Demonstrate new tools and workflows to technical and non-technical teams. - Explain technical concepts and business value in clear, practical language. - Create documentation, playbooks and reusable templates. - Support internal training sessions and workshops. - Gather feedback from users and turn it into meaningful product and workflow improvements. - Help teams understand where AI is useful, where human review is required and where automation is not appropriate. 4. Support the engineering team - Mentor junior AI engineers through pairing, code review and technical guidance. - Help junior team members improve their Python, Git, testing and debugging skills. - Break larger projects into clear, deliverable engineering tasks. - Promote reviewable code, disciplined version control and reliable delivery practices. - Share knowledge openly and contribute to a collaborative engineering culture. Who we’re looking for You’re an experienced engineer who enjoys turning ambiguous business problems into dependable production systems. You ship working software rather than prototypes that remain on a branch. You’re comfortable moving between architecture, implementation, testing and production support. You can open an unfamiliar codebase, trace a problem and explain both the cause and the fix. You understand that successful AI engineering isn’t only about prompting a model. It also requires reliable data, thoughtful evaluation, sensible cost controls, good software engineering and workflows that people will actually use. You also enjoy helping others. You can communicate confidently with non-engineers, demonstrate your work and help colleagues adopt new tools without unnecessary technical language. Requirements Must have - Strong, production-level Python experience. - Experience designing, building, testing and maintaining production applications or automation systems. - Practical experience shipping LLM-based features beyond the prototype stage. - Experience with prompting, structured outputs, output evaluation and model-quality testing. - An understanding of LLM cost, quality, latency and reliability trade-offs. - Hands-on experience with models or providers such as GPT, DeepSeek, OpenRouter or similar. - Strong knowledge of REST APIs, authentication and external-system integrations. - Experience building scheduled jobs and robust data pipelines. - A sound understanding of retries, timeouts, rate limits, validation, logging and error handling. - Experience building idempotent workflows that can safely survive a rerun. - CRM integration experience, ideally with HubSpot. - Experience integrating multiple external systems, such as CRMs, marketing platforms, databases, payment platforms or other SaaS APIs. - The ability to explain the authentication model, data structure and operational quirks of systems you have integrated. - Strong GitHub experience, including branches, pull requests, code reviews and GitHub Actions or comparable CI tooling. - Experience writing automated tests and using CI checks to protect production systems. - Confidence working in unfamiliar codebases and debugging live issues. - Clear written and verbal communication skills. - Confidence demonstrating technical work to non-technical audiences. - Experience mentoring or supporting less-experienced engineers. Nice to have - Experience building or directing internal dashboards and tools. - Working knowledge of React or another modern front-end framework. - Experience with cloud infrastructure, containers or serverless deployment. - Experience with queues, background workers and event-driven systems. - Familiarity with LLM observability, evaluation frameworks or prompt/version management. - Experience implementing human-review or approval workflows around AI-generated outputs. - Knowledge of data privacy, access control and secure handling of client data. - Digital-marketing or agency experience, particularly in SEO, PPC or lead-generation funnels. What good looks like In this role, you will: - Ship AI and automation systems that are used in day-to-day operations. - Build workflows that are reliable, measurable and maintainable. - Reduce repetitive manual work without creating fragile dependencies. - Improve the quality of the team’s code through testing, review and reusable engineering patterns. - Help junior engineers become more capable and independent. - Make model and technology decisions based on evidence—not hype. - Help non-technical teams understand and confidently use the systems you build. - Leave behind documentation and processes that enable others to operate and improve your work. Why First Page? - Real production impact: The systems you build will serve real teams and clients. - Measurable outcomes: Your work will be tied to time saved, quality improved, revenue generated or operational risk reduced. - Meaningful technical ownership: You’ll influence architecture, model selection and engineering standards. - Freedom to choose the right tools: Work with GPT, DeepSeek, OpenRouter and other models and services based on their suitability. - Fast decision-making: You’ll work in a small team where strong ideas can move quickly into production. - A substantial automation roadmap: There is a steady stream of internal workflows ready to be improved. - Growth and leadership opportunities: You’ll mentor junior engineers and have room to expand your technical ownership.

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