Engineering Lead for AI Solutions

HSBC Global Services Limited; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

A leading financial services organization in Singapore seeks an Engineering Lead for AI Solutions. This role involves strategic leadership in developing scalable systems, integrating AI/ML capabilities, and mentoring engineering teams. Open to candidates with strong backgrounds in cloud platforms, microservices, and technical leadership. The successful applicant will play a critical part in shaping innovative solutions, driving operational excellence, and ensuring compliance with regulatory standards.

Benefits

Flexible working

Professional development opportunities

Inclusive workplace environment

Qualifications

• Demonstrated ability to lead technical deep dives.
• Strong ability to facilitate architecture reviews.
• Proven experience in coordinating remediation across teams.

Responsibilities

• Act as the technical owner for core platform domains.
• Lead targeted technical deep-dives.
• Collaborate with product, security, data, and ops.

Skills

Technical leadership

Microservices architecture

AI/ML integration

DevOps practices

Cloud infrastructure

Education

University degree in Computer Science

Cloud certification preferred

Tools

Apache Kafka

Terraform

AWS

Azure

GCP

Job description

Some careers open more doors than others.

If you’re looking for a career that will unlock new opportunities, join HSBC and experience the possibilities. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

Our GCIO organisation plays a critical role for the bank. This team partners with the businesses to build the platforms, systems, and products that our customers use every day. We keep people’s money and data safe, and are at the forefront of driving innovation for our businesses, customers, and colleagues.

We are currently seeking a high calibre professional to join our team as an Engineering Lead for AI Solutions.

Role Purpose

The Engineering lead for Emerging Technology WPS will lead the Emerging Tech for iWPB Wealth & Premier Solutions, driving technical excellence, operational resilience and engineering innovation. This role will own architecture and delivery of scalable, high‑performance systems, mentor teams, lead technical deep dives and root‑cause analysis, and take accountability for Tech Risk Control book‑of‑work tasks to ensure risk, compliance and remediation are delivered to programme standards.

Principal Responsibilities

• Provide strategic technical leadership across engineering projects, ensuring alignment with business goals, architecture principles and regulatory/compliance requirements.
• Architect and design scalable, resilient, secure microservices and event-driven systems to support high-throughput financial services workloads.
• Lead adoption and governance of engineering standards, patterns and best practices (API design, domain-driven design, CI/CD).
• Hands‑on development and code review in core platforms; set standards for software craftsmanship across Morden Tech stacks and cloud-native services.
• Mentor and coach senior engineers and engineering leads; run regular technical deep dives, architecture reviews and cross-team workshops.
• Lead and facilitate blameless post-mortems and structured root cause analysis (RCA), driving remediation plans and lessons learned into the development lifecycle.
• Own the Tech Risk Control “book of work”: maintain backlog of control remediation tasks, coordinate with Risk/Compliance to define mitigations, track progress, and ensure audit readiness.
• Drive the integration of AI/ML capabilities into production systems with appropriate controls for governance, model risk, explainability and data privacy.
• Collaborate with product, security, ops and data teams to prioritise technical debt, reliability improvements and platform investments.
• Represent engineering in stakeholder forums, technical governance boards and external partner engagements.
• Strategic regional hub: Singapore’s location and ecosystem provide exposure to both East and West tech trends — access to APAC innovation while maintaining close ties to global (US/Asia) technology partners and standards.
• Global vision & collaboration: Work with diverse, multinational teams and partners across timezones, enabling cross-regional product strategies, faster international rollouts and broader market insights.
• Talent & research connectivity: Strong links to leading universities, research centres and fintech clusters across Asia and the West, plus a multilingual talent pool and regulatory clarity that support global-grade engineering and compliance.

What you will be doing

• Act as the technical owner for core platform domains, driving architecture, design and delivery across backend, data streaming and cloud infrastructure; focus deeply on 2–3 areas (e.g., Java/Spring, Kafka/Stream Processing, Cloud/Kubernetes).
• Lead targeted technical deep-dives (2–3 per quarter) to resolve architectural trade-offs, eliminate chronic pain points and transfer knowledge across teams.
• Own and deliver the Tech Risk Control book‑of‑work items for your area: define remediations, coordinate cross-functional delivery, produce evidence for audits and close out controls.
• Run structured root‑cause analysis and blameless post‑mortems for major incidents, translate findings into prioritized fixes, and ensure follow‑through.
• Provide hands‑on technical direction: participate in design reviews, code reviews, prototyping and proof‑of‑concepts to validate architecture decisions.
• Mentor senior engineers and engineering leads; raise team capability through coaching, workshops and documented standards/patterns.
• Collaborate with product, security, data and ops to align technical strategy with business objectives, regulatory requirements and non‑functional goals (scalability, resilience, security).
• Drive adoption of cloud-native and DevOps practices (CI/CD, observability) and ensure production readiness for new services and AI/ML components.

Leadership & Teamwork

• Demonstrated ability to lead technical deep dives, facilitate architecture reviews and drive team learning through hands‑on tech sessions.
• Strong facilitation of RCA and incident response processes; experience running blameless post‑mortems and converting findings into concrete remediation (tracked in the Tech Risk Control book‑of‑work).
• Experience coordinating remediation across engineering, ops and risk teams; comfortable owning risk remediation delivery, SLAs and evidence for audits.
• Excellent stakeholder communication and ability to translate complex technical trade‑offs for senior business and compliance audiences.
• Track record of driving engineering transformation: introducing modern patterns (microservices, DevOps, platform engineering), and uplifting team capability.

Certifications & Education

• University degree in Computer Science, Engineering or related discipline; MSc/PhD preferred.
• Cloud certification(s) strongly preferred: AWS Certified Solutions Architect Professional or DevOps Engineer, Microsoft Certified: Azure Solutions Architect, or Google Professional Cloud Architect.
• Desirable: Kubernetes (CKA/CKAD), security or data governance certificates.

Preferred Qualifications

• Experience in financial services or regulated industries with demonstrable knowledge of regulatory controls, audit preparation and model risk governance.
• Contributions to open source projects or academic/industry research; speaker at technical conferences is a plus.
• Proven ability to lead cross‑functional engineering teams through technological transformations, and to operationalise AI safely at scale.

Deliverables & Success Measures

• Architecture and platform designs that meet non‑functional requirements (scalability, resiliency, security).
• Successful delivery of prioritized Tech Risk Control book‑of‑work items and remediation actions.
• Reduction in incident mean‑time‑to‑detect and mean‑time‑to‑recover through improved observability, RCA and runbooks.
• Mature AI/ML deployment pipelines with documented governance, monitoring and model lifecycle controls.
• High team engagement, evidence of knowledge transfer via deep dive sessions and measurable uplift in engineering capability.

Technical Skills & Experience

Familiar on one or more tech skill.

• Event streaming and messaging: Apache Kafka (Kafka Streams, ksqlDB), Confluent tooling and best practices for exactly‑once semantics and fault-tolerant processing.
• Data platform familiarity: batch/stream processing (Spark, Flink), data lakehouse concepts (Delta Lake), and data governance tools (e.g. Apache Atlas, Apache Falcon or equivalent).
• AI / ML / LLM productionisation: hands‑on with MLOps and Model frameworks (LangGraph, Agent Development Kit, Microsoft Agent Framework ); experience deploying and operating LLMs (e.g., Falcon family or other LLMs), embeddings, RAG architectures and frameworks (LangChain, LlamaIndex).
• Observability, reliability and performance engineering: Prometheus/Grafana, ELK/EFK, distributed tracing (Jaeger/Zipkin), profiling and tuning high‑throughput systems.
• DevOps, CI/CD: Terraform, Ansible , G3 , and SonarQube.
• Cloud platforms: proven experience on at least one major public cloud (AWS, Azure or GCP) in production scale environments.
• Security, compliance & risk controls: secure coding practices, threat modelling, encryption, key management and OWASP mitigation patterns.

Opening up a world of opportunity

www.hsbc.com/careers

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Issued by The Hongkong and Shanghai Banking Corporation Limited