TymeX
About the Role
TymeX is building one of the most advanced Data & AI platforms in digital banking. A core pillar of this platform is a
unified semantic layer
that ensures every data product across our domains is interoperable, trustworthy, and AI-ready. As a
Semantics Architect , you will design and govern this semantic backbone across domains and countries. Your work will directly power dynamic customer 360, conversational analytics, accurate LLM retrieval, and actionable AI agents across the bank.
This is a rare opportunity to define a semantic architecture from the ground up to safely unleash AI Agents and automation at industrial scale.
What You'll Do
Own and evolve the Semantic Architecture for the Bank
Design, maintain, and govern an AI‑ready semantic architecture and underlying technical framework
Work with domain experts and architects to establish naming conventions, ontologies, and data modelling rules & taxonomies
Build and maintain a canonical model that enables dynamic reconstruction of entire customer journeys across products and channels
Define the domain event ontology and event schemas, ensuring consistent semantics across transactional, behavioural, and system events
Determine a robust metadata architecture and framework and ensure seamless integration with the foundation data platform Databricks
Define and manage the semantic runtime, ensuring semantic definitions are performant, executable, testable, queryable, and consistently applied across ETL, feature pipelines, LLM retrieval workflows, MCP Server, and real‑time APIs
Design the semantic graph (entities, relationships, hierarchies, business rules) that underpins reasoning, AI retrieval, event linking, and customer journey reconstruction & AI action
Develop a framework to embed semantics capture through data product development in a frictionless and consistent manner
Develop intelligent AI‑assisted solutions to ensure semantic consistency with Data Product or Domain SME in the loop
Develop solutions to detect and remediate semantic drift
Own the product roadmap for semantic tooling & frameworks – e.g., semantic catalog, semantic contract validator, lineage resolver, semantic drift detector, ontology editing/visualisation tools, canonical model builder
Define the Semantic and Data Architecture for shared data products such as Master Data, Reference Data, Feature Store, Regulatory Data Products, Core Product data (User, Session, Channel)
Ensure interoperable, distributed ownership aligned with Data Mesh principles wherever practical
Design the semantics layer to power both classic and modern AI (LLM) workloads and use cases
Define semantic grounding strategies for LLMs, enabling hybrid retrieval (SQL + vector + ontology), context resolution, and reliable semantic augmentation for AI agents
Develop a semantics layer that powers reliable and trustworthy conversational analytics (e.g., AI Genie in Databricks or custom AI conversational data agents)
Enable frameworks to ensure efficient and effective semantic consumption as part of context engineering and machine learning
Coach DPOs, stewards, architects, and engineers on semantic best practices
Define templates, frameworks, and accelerators for platform teams to enable automation
Drive reusable semantic building blocks across product teams
Collaborate with platform, governance, and engineering teams to turn ideas into reality
Ensure semantics integrate with Databricks, Unity Catalog, DLT, dbt, and AI tools
Align semantic models with quality, security, lineage, and access policies
Requirements / Qualifications
Master’s degree in a relevant field
5+ years of hands‑on experience in semantic or ontology or data modelling
Proven experience delivering semantics and metadata at scale for large AI workloads
Experience with hyper‑scalar data platforms, semantic tools, dbt, LookML, MDX, Delta Lake, Spark, SQL, Palantir
Strong understanding of data contracts and data quality frameworks
Strong understanding of Data Mesh Principles and the socio‑technical changes required to democratise data
Experience building analytics, ML, or AI‑driven systems with semantics inputs
Hands‑on builder‑leader who is not shy of building frameworks to accelerate understanding and development processes and turn ideas into reality
Strong communication and stakeholder alignment skills
Passion for modern AI and reusable data ecosystems
Benefits
Performance bonus up to 2 months
13th month salary (pro‑ratio)
15 days annual leave + 3 sick days + birthday leave + Christmas leave
Meal & parking allowance
Full salary & benefits during probation
Premium healthcare for you and your family
Growth pathways, conferences, and continuous learning
International, values‑driven culture
Overseas travel opportunities
Internal hackathons, team events, Blue Card programme
40‑hour week, Monday‑Friday
Relocation offered to Vietnam; strong candidates overseas may be considered for remote location
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Other
Industries IT Services and IT Consulting
#J-18808-Ljbffr
unified semantic layer
that ensures every data product across our domains is interoperable, trustworthy, and AI-ready. As a
Semantics Architect , you will design and govern this semantic backbone across domains and countries. Your work will directly power dynamic customer 360, conversational analytics, accurate LLM retrieval, and actionable AI agents across the bank.
This is a rare opportunity to define a semantic architecture from the ground up to safely unleash AI Agents and automation at industrial scale.
What You'll Do
Own and evolve the Semantic Architecture for the Bank
Design, maintain, and govern an AI‑ready semantic architecture and underlying technical framework
Work with domain experts and architects to establish naming conventions, ontologies, and data modelling rules & taxonomies
Build and maintain a canonical model that enables dynamic reconstruction of entire customer journeys across products and channels
Define the domain event ontology and event schemas, ensuring consistent semantics across transactional, behavioural, and system events
Determine a robust metadata architecture and framework and ensure seamless integration with the foundation data platform Databricks
Define and manage the semantic runtime, ensuring semantic definitions are performant, executable, testable, queryable, and consistently applied across ETL, feature pipelines, LLM retrieval workflows, MCP Server, and real‑time APIs
Design the semantic graph (entities, relationships, hierarchies, business rules) that underpins reasoning, AI retrieval, event linking, and customer journey reconstruction & AI action
Develop a framework to embed semantics capture through data product development in a frictionless and consistent manner
Develop intelligent AI‑assisted solutions to ensure semantic consistency with Data Product or Domain SME in the loop
Develop solutions to detect and remediate semantic drift
Own the product roadmap for semantic tooling & frameworks – e.g., semantic catalog, semantic contract validator, lineage resolver, semantic drift detector, ontology editing/visualisation tools, canonical model builder
Define the Semantic and Data Architecture for shared data products such as Master Data, Reference Data, Feature Store, Regulatory Data Products, Core Product data (User, Session, Channel)
Ensure interoperable, distributed ownership aligned with Data Mesh principles wherever practical
Design the semantics layer to power both classic and modern AI (LLM) workloads and use cases
Define semantic grounding strategies for LLMs, enabling hybrid retrieval (SQL + vector + ontology), context resolution, and reliable semantic augmentation for AI agents
Develop a semantics layer that powers reliable and trustworthy conversational analytics (e.g., AI Genie in Databricks or custom AI conversational data agents)
Enable frameworks to ensure efficient and effective semantic consumption as part of context engineering and machine learning
Coach DPOs, stewards, architects, and engineers on semantic best practices
Define templates, frameworks, and accelerators for platform teams to enable automation
Drive reusable semantic building blocks across product teams
Collaborate with platform, governance, and engineering teams to turn ideas into reality
Ensure semantics integrate with Databricks, Unity Catalog, DLT, dbt, and AI tools
Align semantic models with quality, security, lineage, and access policies
Requirements / Qualifications
Master’s degree in a relevant field
5+ years of hands‑on experience in semantic or ontology or data modelling
Proven experience delivering semantics and metadata at scale for large AI workloads
Experience with hyper‑scalar data platforms, semantic tools, dbt, LookML, MDX, Delta Lake, Spark, SQL, Palantir
Strong understanding of data contracts and data quality frameworks
Strong understanding of Data Mesh Principles and the socio‑technical changes required to democratise data
Experience building analytics, ML, or AI‑driven systems with semantics inputs
Hands‑on builder‑leader who is not shy of building frameworks to accelerate understanding and development processes and turn ideas into reality
Strong communication and stakeholder alignment skills
Passion for modern AI and reusable data ecosystems
Benefits
Performance bonus up to 2 months
13th month salary (pro‑ratio)
15 days annual leave + 3 sick days + birthday leave + Christmas leave
Meal & parking allowance
Full salary & benefits during probation
Premium healthcare for you and your family
Growth pathways, conferences, and continuous learning
International, values‑driven culture
Overseas travel opportunities
Internal hackathons, team events, Blue Card programme
40‑hour week, Monday‑Friday
Relocation offered to Vietnam; strong candidates overseas may be considered for remote location
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Other
Industries IT Services and IT Consulting
#J-18808-Ljbffr