18 hours ago
Bengaluru, IndiaStaff+

Responsibilities

  • Design and build enterprise-scale knowledge products that transform unstructured information into trusted, reusable, AI-ready assets.
  • Develop and maintain ontologies, semantic models, metadata, taxonomies, and knowledge graphs across business domains.
  • Engineer knowledge ingestion, enrichment, retrieval, and lifecycle-management capabilities for governed knowledge products.
  • Implement governance controls for ownership, lineage, provenance, classification, permissions, auditability, and lifecycle policies.
  • Build policy-as-code, deterministic decisioning, AI guardrails, retrieval controls, and policy-aware access mechanisms.
  • Integrate knowledge platforms with LLM gateways, agent frameworks, evaluation frameworks, AI platform services, and model-orchestration services.
  • Establish quality, observability, evaluation, and feedback loops to improve knowledge accuracy and retrieval effectiveness.
  • Collaborate with engineering, CAIO, CDO, product, business, and knowledge-owner stakeholders.

Requirements

  • Deep expertise in knowledge graphs, ontology engineering, semantic modelling, taxonomy, and metadata management.
  • Experience with unstructured data processing, document understanding, information extraction, entity resolution, and knowledge-enrichment pipelines.
  • Hands-on expertise in RAG, GraphRAG, vector databases, search technologies, and retrieval optimisation.
  • Knowledge of RDF, OWL, SKOS, SPARQL, Neo4j, Amazon Neptune, and graph-modelling concepts.
  • Experience designing scalable, reliable, observable, secure, cloud-native enterprise knowledge platforms and integration APIs.
  • Understanding of data governance, lineage, provenance, access control, compliance, permissions, classification, and auditability frameworks.
  • Experience implementing AI guardrails, retrieval controls, policy-aware access, evaluation mechanisms, and governance controls.
  • Experience integrating LLM gateways, agent frameworks, AI platforms, guardrails, evaluation frameworks, and model-orchestration services.
  • Ability to implement policy-as-code, executable knowledge, rules engines, and deterministic decisioning; BPMN and DMN experience is desirable.
  • Strong programming experience with Python, TypeScript/Node.js, and SQL.
  • Familiarity with agentic AI architectures, multi-agent orchestration, MCP patterns, tool-based reasoning, process intelligence, process mining, business capability modelling, and decision modelling is desirable.
  • Bachelor’s or master’s degree in engineering, computer science, applied mathematics, statistics, or a related discipline.
  • Relevant AWS, AI/ML, or Generative AI certifications are advantageous.

Benefits

  • Location: Bangalore.
  • Relevant cloud or AI certifications are supported as advantageous qualifications.
  • Applications from Commonwealth Bank Group employees must be submitted through Sidekick.
  • Accessibility support is available through HR Direct.
Commonwealth Bank of Australia

About Commonwealth Bank of Australia

10,000+ employees

Commonwealth Bank of Australia is an ASX-listed bank headquartered in Sydney that provides retail, business, and institutional banking, payments, and wealth services across Australia. Its offerings include transaction and savings accounts, home and business lending, cards, merchant services, digital banking, superannuation, and investment platforms such as CommSec. Founded in 1911, the bank serves millions of customers through branches, contact centres, and online channels.

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