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Associate Director, Software Engineering
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Bachelor's degree or above in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology, or a related technical discipline, or equivalent practical experien
- Solid professional experience in software engineering, AI engineering, or related technical delivery roles, with a strong record of building and productionising enterprise systems.
- Strong hands on programming capability in Python, and experience with at least one additional enterprise development language or ecosystem such as JavaScript / TypeScript, Java, C#, or Go.
- Practical understanding of AI / Machine Learning (ML) and LLM application architectures, including RAG, embeddings, prompt orchestration, model APIs, evaluation, and guardrails.
- Proven track record of delivering production systems such as backend services, APIs, data integrations, web applications, or automation platforms in complex environments.
- Good knowledge of architecture and engineering practices including distributed systems, integration patterns, security, observability, CI/CD, and operational support.
- Strong communication skills, with the ability to explain technical topics clearly to business stakeholders and collaborate effectively across teams.
- Strong ownership mindset and willingness to stay hands on in code, design, troubleshooting, and production readiness.
Full description
Some careers have more impact than others.
If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be.
We are currently seeking an experienced professional to join our team in the role of Associate Director, Software Engineering.
Business:Chief AI OfficePrincipal responsibilities
- Design, build, and deliver AI enabled solutions covering LLM powered features, RAG based knowledge solutions, agentic workflows, automation platforms, Application Programming Interfaces (APIs), and user facing enterprise applications.
- Partner with business stakeholders and senior engineers to understand operational workflows, identify high value AI opportunities, and shape practical delivery plans.
- Translate business requirements into clear technical designs covering AI / LLM integration, data flows, APIs, security controls, and deployment models.
- Develop production grade software using technologies such as Python, JavaScript / TypeScript, backend services, databases, cloud platforms, and containers.
- Apply engineering standards for testing, Continuous Integration / Continuous Delivery (CI/CD), logging, monitoring, and evaluation of AI solution quality and performance.
- Collaborate with product managers, AI researchers, data scientists, enterprise architects, cyber security, risk, and compliance teams to ensure solutions are safe, scalable, and enterprise ready.
- Support production rollout, monitoring, troubleshooting, and continuous improvement of deployed AI solutions.
- Share knowledge with teammates through code reviews, design discussions, and delivery best practice sharing.
Requirements
- Bachelor's degree or above in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology, or a related technical discipline, or equivalent practical experience.
- Solid professional experience in software engineering, AI engineering, or related technical delivery roles, with a strong record of building and productionising enterprise systems.
- Strong hands on programming capability in Python, and experience with at least one additional enterprise development language or ecosystem such as JavaScript / TypeScript, Java, C#, or Go.
- Practical understanding of AI / Machine Learning (ML) and LLM application architectures, including RAG, embeddings, prompt orchestration, model APIs, evaluation, and guardrails.
- Proven track record of delivering production systems such as backend services, APIs, data integrations, web applications, or automation platforms in complex environments.