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 organizations 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 realize their ambitions.
We are currently seeking an experienced professional to join our team in the role of Associate Director, Software Engineering Specialist
Key Responsibilities
Lead design, implementation, and scaling of enterprise AI safety & security guardrail services (LLM + agent ecosystems). Combine deep AI safety engineering with high-performance Python backend (FastAPI/Django), container/Kubernetes operations, and crossfunctional stakeholder alignment (Cybersecurity, Model Risk Management, Privacy, Compliance). Drive vendor collaboration and internal architecture strategy for resilient, auditable, low-latency guardrail enforcement.
- Own technical architecture for multi-layer guardrails: request pre-processing, model mediation, post-output validation, agent step auditing.
- Design/extend services for: jailbreak & prompt/indirect injection detection, retrieval poisoning defense, PII detection/redaction/masking/tokenization, toxicity/hate/harassment/self-harm/extremism filtering, data loss prevention (secrets, source provenance, outbound scanning), sensitive credential scanning, hallucination/factuality/citation enforcement, misinformation (medical/financial), regulatory compliance filters, copyright/IP/brand safety, policy orchestration (allow/block/redact/escalate/human review), agent session safety (tool invocation constraints, multi-step trace auditing), metrics & experimentation APIs.
- Architect Python microservices (FastAPI/Django, async I/O, streaming) with versioned policies, feature flags, canary and shadow deployments.
- Build evaluation framework: automated red-teaming suites, adversarial scenario generation, precision/recall/F1 dashboards, safety regression gates, latency/cost profiling, drift (content, behavior, model) detection.
- Integrate ML/NLP components (Presidio, spaCy, Hugging Face, vector similarity, custom classifiers, rule + ML ensembles, entropy and checksum validators).
- Productionize RAG safety: document provenance scoring, source trust tiers, citation completeness, leakage prevention.
- Implement full observability: structured audit logs, OpenTelemetry tracing, Prometheus metrics (guardrail hit ratios, decision distributions, latency percentiles), incident classification feeds.
- Harden services: authN/Z (OIDC/OAuth2, service principals), rate limiting, circuit breakers, sandboxing, secure config/secrets, runtime isolation, network policies, API contract governance.
- Lead Docker/Kubernetes strategy: multi-stage builds, image minimization, SBOM, Helm/Kustomize, HPA/autoscaling policies, PodSecurity, resource tuning, rollback playbooks.
- Coordinate requirements with Cybersecurity, Model Risk Management, Privacy, Compliance, Legaltranslate policies into executable rules and evaluators.
- Run stakeholder UAT cycles: test planning, evidence collection, false-positive adjudication, iterative tuning.
- Manage vendor engagements: technical due diligence, integration interfaces, performance/SLA validation, joint solution design and escalation paths.
- Mentor engineering teams; establish coding standards, review protocols, architecture decision records, incident runbooks.
To be successful in this role you should meet the following requirements
- Bachelor's degree in Computer Science/Engineering
- 12+ years software engineering (majority in Python) with 5+ years focused on AI/ML or content safety/security.
- Proven delivery of large-scale guardrail or trust/safety platforms for LLMs or high-risk content systems.
- Deep FastAPI/Django, async patterns, streaming moderation, middleware pipelines.
- Strong ML/NLP integration experience: pattern + ML hybrid detectors, evaluator services, vector stores.
- Kubernetes production operations (autoscaling, resilience, security hardening) and CI/CD (policy gates, security scanning, artifact signing).
- Advanced observability and performance tuning (profilers, tracing, queue/backpressure management, caching strategies).
- Risk & compliance alignment (MRM validation workflows, audit evidence, model governance).
- Vendor technical management (RFP criteria, integration architectures, SLA/perf oversight).
- Candidate with less relevant experience or skills may be offered a lower Global Career Band than stated above.
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.
