HSBC
Website:
hsbc.com
Company:
https://www.linkedin.com/company/hsbc
Industries: Financial Services
Job details:
Some careers shine brighter than others.
If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. 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.
HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 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 realise their ambitions.
We are currently seeking an experienced professional to join our team in the role of Consultant Specialist
As a Google Cloud Infrastructure / DevOps Engineer, you will be responsible for designing, implementing, and maintaining our cloud infrastructure while ensuring efficient development operations. Your role bridges the gap between development and operations, focusing on automation, scalability, and reliability. You’ll collaborate with cross-functional teams to optimize our systems and enhance delivery pipelines.
We value core IaC (Terraform and Helm) and core Kubernetes skills, solid experiences in building data platform in GCP would be a big plus
In This Role, You Will
- Manage and monitor core GCP services, ensuring stable day-to-day cloud operations.
- Design and operate scalable, highly available, and secure cloud infrastructure on Google Cloud.
- Build and maintain CI/CD pipelines to enable fast, reliable application releases.
- Automate build/test/deploy/rollback workflows and improve deployment efficiency with engineering teams.
- Implement Infrastructure as Code using Terraform (and Helm where applicable) with version control and repeatable environments.
- Establish monitoring, alerting, and observability; troubleshoot infra and pipeline issues to restore service quickly.
- Drive security-by-design and compliance adherence, partnering with security and documenting architectures/runbooks.
- Develop and optimise RAG solutions: document ingestion, chunking strategies, embedding workflows, vector search, reranking, and citation/traceability.
- Implement evaluation and testing for AI systems: offline test sets, regression suites, adversarial testing (prompt injection/jailbreak), and quality metrics.
- Establish MLOps/LLMOps practices: CI/CD for AI components, versioning (prompts/models/data), automated checks, and controlled releases (canary/rollback).
To be successful in this role, candidate should meet the following requirements:
- Bachelor’s degree in Computer Science/IT (or equivalent practical experience).
- 5+ years of industry experience, including 3+ years designing and running production systems on GCP. Strong hands-on Kubernetes/GKE and containerization (Docker) experience; microservices understanding.
- Solid IaC skills with Terraform and Helm; able to standardize dev/stage/prod environments. CI/CD expertise with Jenkins (or similar tooling) and DevOps best practices. Scripting proficiency in Python and/or Bash for automation.
- Familiarity with key GCP services (e.g., Compute Engine, GKE, Cloud Storage, BigQuery, IAM) and event streaming (Kafka and/or Pub/Sub); data platform experience on GCP is a plus.
- Strong software engineering fundamentals: system design, API design, distributed systems, and clean coding practices. Hands-on experience delivering production-grade AI solutions, including at least one of:
- LLM integrations (prompt orchestration, tool/function calling, structured outputs), or ML model deployment/inference services, or Search/RAG and knowledge retrieval platforms. Proficiency in Python plus at least one backend language (e.g., Java, Go, C#, TypeScript).
- Experience with modern deployment practices: containers (Docker), CI/CD, and cloud-native services. Experience with vector search technologies (e.g., OpenSearch/Elastic, pgvector, FAISS, Pinecone) and embedding/reranking techniques. Familiarity with LLM frameworks/patterns (e.g., LangChain, LlamaIndex) and prompt versioning/evaluation tooling.
- Knowledge of performance optimization techniques: caching, batching, rate limiting, quantisation, latency/cost tuning. Background in regulated environments with strong governance and auditability requirements.
You’ll achieve more when you join HSBC.
www.hsbc.com/careers
HSBC is 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. 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
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