Principal Engineer

Some careers have more impact than others.

If you’re looking for further opportunities to develop your career, take the next step in fulfilling your potential right here at HSBC.

HSBC is one of the largest banking and financial services organizations in the world, with operations in 58 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realize their ambitions.

We are currently seeking an experienced professional to join our team in the role of Principal Engineer.

The Opportunity:

Your primary responsibility is to be the beacon of `Engineering Excellence’ across the entire of HSBC’s IWPB areas. You will demonstrate a passion for designing and delivering quality software efficiently (ideally, zero toil, zero defects). The candidate will drive high standards across the department and be a role model exemplifying these standards. The candidate will be able to develop and communicate technical strategy and influence senior stakeholders in the delivery of IT solutions aligned to HSBC Technology’s strategic vision.

This position plays an instrumental role in driving technical delivery and best in class design & code across a portfolio of agile teams.

There is a specific emphasis on building Android and iOS Mobile Native App Development (using Kotlin, Swift), and using containerization for multiple cloud deployments, coupled with an inner source and pattern-based approach to promote consistency and reusability. For this to be successful, pods will need to sustain a high degree of engineering discipline. The Principal Engineer is the key role that facilitates and enables this.

This role demands someone with hands on engineering leadership. They will have a deep awareness of technology, best practices and emerging trends across the industry. They will be able to mobilize ideas safely within the controlled framework we operate in.

What you’ll do:

• Engineering / Software delivery

1. 1. Be the beacon of “Engineering Excellence” across the entire of IWPB.
   2. Drive technical delivery with best-in-class design & code across a wide range of portfolio of agile teams.
   3. Design and deliver quality software efficiently (aiming for “zero toil”, and "zero defects").

• Translate business opportunities into technical solutions.

1. 1. Choose the “right tool for the job” across modern programming languages.
   2. Constructively challenge existing thinking and develop improved paths forward.
   3. Platform / Cloud / Containerization / Microservices / Android and iOS Mobile Native App Development (using Kotlin, Swift)
   4. Apply microservice design and containerized solutions, or build world-class Android and iOS Mobile Native Apps (using Kotlin, Swift).
   5. Promote/enable containerization for multiple cloud deployments; support a pattern-based approach to consistency and reusability, and in Android and iOS Mobile Native App Development (using Kotlin, Swift).
   6. Design and run highly available systems at scale / highly available systems (e.g. banking apps & services).

• DevOps / Automation / Reliability / Incident management

1. 1. Consider automation from the start to reduce toil.
   2. Navigate production incidents swiftly to get to root cause; drive improvements.
   3. Champion DORA and other engineering metrics; improve KPIs over time.

• Strategy / Stakeholder management / Influence

1. 1. Develop and communicate technical strategy aligned to HSBC Technology’s strategic vision.
   2. Influence senior stakeholders in delivery of IT solutions.
   3. Build relationships with key stakeholders and technology partners.
   4. Explain technology well to business/senior managers to gain buy-in to a technology direction.
   5. Identify risks and opportunities for the business.
   6. Influence beyond the immediate department / (wherever possible, and with right governance) beyond HSBC in the industry as well.

• Community building / Leadership / Capability uplift

1. 1. Build and lead communities that “raise the bar” on quality and efficiency.
   2. Coach, Mentor and share knowledge with others. Build SMEs.
   3. Support Engineering Leads to identify solutions to engineering gaps/challenges.
   4. Facilitate development of cross-functional capabilities to address common gaps/challenges.
   5. Lead others to change behaviors / transfer expertise.
   6. Continuously improve self and team; value team success over individual success.

• Research / Continuous improvement

1. 1. Research new tech/processes and drive adoption.
   2. Stay up-to-date and guide the engineering community on evolving trends.
   3. Think a few steps forward and guide team/department to a new direction.

• AI / Data / ML enablement

1. 1. Act as a trusted partner with Business, accelerating AI adoption.
   2. Partner with business and engineering teams to identify high-value AI use cases (e.g., Finance insights, Customer & Staff Benefits, Risks, Controls, regulatory reporting, operational efficiency) and translate them into deliverable roadmaps.
   3. Shape and govern AI solution design choices (build vs buy, model selection, prompt strategy, RAG vs fine-tuning) with clear trade-offs on risk, cost, latency and maintainability.
   4. Embed Responsible AI practices into delivery (fairness, explainability, privacy, security, human-in-the-loop) and ensure solutions meet HSBC governance expectations.
   5. Establish AI engineering patterns and reusable components (prompt templates, evaluation harnesses, feature stores/embeddings patterns, model gateways) to accelerate delivery across teams.
   6. Drive AI quality and performance management: define evaluation metrics, run offline/online tests, monitor drift, and continuously improve model outcomes.
   7. Enable AI adoption at scale by coaching teams on AI engineering practices and setting standards for documentation, testing, and operational readiness.
   8. Work with platform teams to ensure AI workloads are production-ready (scalable inference, cost controls, observability, resilience, and incident response).

What you will need to succeed in the role:

• Hands-on engineering

1. 1. Hands-on, passionate technologist; actively coding (~70% coding).
   2. Deep awareness of technology, best practices, and emerging industry trends.
   3. Strong problem-solving; pragmatic delivery while aligning to longer-term strategy.
   4. Comfortable with ambiguity in requirements/design/outcomes.
   5. “Communicate with code”.

• Programming languages / Technical breadth

1. 1. Strong in Java/Kotlin/Swift and hands-on coding experience.
   2. Broad capability across modern programming languages; can select the right tool.
   3. Generalist / “T-shaped engineer”; not only a single-domain specialist.

• Cloud / Containers / Kubernetes / Microservices / Native Mobile Apps / Android and iOS Mobile Native App Development (using Kotlin, Swift)

1. 1. Hands-on expertise in either Kubernetes/Cloud, or in Kotlin and/or Swift for Native Android and iOS Development of Mobile Apps.
   2. Microservices design + containerized solutions, or well-versed in Android and iOS Mobile Native App Development (using Kotlin, Swift).
   3. Ability to follow full-stack shifts including containers, Kubernetes, cloud, data lakes, storage, networking, or Android and iOS Mobile Native App Development (using Kotlin, Swift).
   4. Familiarity deploying solutions to different cloud providers in an agnostic way, or Android and iOS Mobile Native App Development (using Kotlin, Swift).

• Reliability engineering / Operations

1. 1. Experience designing and running highly available systems at scale / highly available systems.
   2. Production incident investigation, root-cause analysis, and strategic problem-solving mindset.

• DevOps / Automation / Engineering metrics

1. 1. Automation-first mindset to reduce toil/time-consuming work; enable faster and secure delivery.
   2. Support/advocacy for DORA and engineering metrics; KPI improvement.

• Architecture / Engineering standards

1. 1. Strong knowledge of IT development methodology, architecture design, engineering solutions, and technical standards.
   2. Open-Source / Engineering culture signals
   3. Evidence of engagement with the wider tech community (blogs/podcasts, GitHub portfolio, open-source contributions).
   4. Awareness of analytic tooling and open-source technologies.

• Leadership / Communication / Influence

1. 1. Ability to develop and communicate technical strategy and direction.
   2. Ability to influence senior stakeholders; explain technology clearly to business/senior managers.
   3. Takes accountability & personal risk (not deferring to “an Architect” or “the process”).
   4. Ability to build relationships with stakeholders/technology partners.
   5. Ability to evangelize/influence engineering best practices.
   6. Communicate ideas succinctly; articulate big-picture vision/strategy/direction.
   7. Ability to think about business impact; holistic problem solving.

• AI / ML / GenAI engineering

1. 1. Working knowledge of modern AI concepts and delivery patterns:
      LLM fundamentals (tokens, context windows, latency/cost trade-offs, hallucinations and mitigation).
      1. RAG patterns (chunking, embeddings, vector search, retrieval quality, grounding/citations).
      2. Prompt engineering and prompt lifecycle management (versioning, testing, guardrails).
      3. Fine-tuning vs prompt/RAG trade-offs; when each is appropriate.
   2. Ability to evaluate AI systems, not just do PoCs and demo them:
      1. Define success metrics (accuracy, faithfulness/grounding, toxicity, bias, latency, cost).
      2. Build evaluation harnesses (golden datasets, regression tests, A/B tests) and monitor drift
   3. Responsible AI awareness:
      1. Data privacy and confidentiality considerations; secure handling of sensitive data.
      2. Explainability, fairness/bias awareness, and human-in-the-loop controls for higher-risk use cases.
      3. Threat awareness (prompt injection, data exfiltration, model misuse) and mitigation approaches.
   4. MLOps/LLMOps mindset:
      1. Model/prompt versioning, reproducibility, release management, and rollback strategies.
      2. Observability for AI services (quality metrics + standard SRE telemetry).
      3. Cost management for inference (caching, batching, rate limiting, model selection)
   5. Practical experience integrating AI into software products:
      1. Building AI-enabled APIs/services, orchestration patterns, and integration with existing microservices.
      2. Using Python effectively for AI prototyping/productionization (even if primary stack is Java/Kotlin/Swift).

You’ll achieve more when you join HSBC.

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.

Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website.

                                                ***Issued By HSBC Software Development (India) Limited***