Job Summary
TECHNICAL JOB DESCRIPTION
• Use Agent Development Kit (ADK), Vertex AI Agent Builder, Model Context Protocol (MCP) servers & clients, Multimodal semantic extraction & inference, GraphRAG & Knowledge graphs, Vector embeddings & Hy... to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope, supported by Knowledge catalogs & AI data governance guardrails.
• Use Ontologies & Semantic schema mapping, PIM/PXM product data enrichment to model, ingest, transform, secure, and serve data using the required scope, supported by BigQuery lakehouse & context-aware data access, Cloud Composer, Dataflow ingestion & retrieval pipelines.
• Use Terraform (IaC module development), GCP landing zones to design, provision, configure, migrate, and tune platform components using the required scope.
• Use IAM & secure pipelines to implement, harden, test, and remediate security and access controls using the required scope.
• Apply Tool orchestration & Function calling as additional skill requirements for this demand.
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Own technical design decisions, code and configuration reviews, and standards for the above tools.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Lead stakeholder alignment, prioritization, and cross-team dependency resolution.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 7 to 10 years of relevant industry experience aligned to the Senior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.
Key Responsibilities
TECHNICAL JOB DESCRIPTION
• Use Agent Development Kit (ADK), Vertex AI Agent Builder, Model Context Protocol (MCP) servers & clients, Multimodal semantic extraction & inference, GraphRAG & Knowledge graphs, Vector embeddings & Hy... to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope, supported by Knowledge catalogs & AI data governance guardrails.
• Use Ontologies & Semantic schema mapping, PIM/PXM product data enrichment to model, ingest, transform, secure, and serve data using the required scope, supported by BigQuery lakehouse & context-aware data access, Cloud Composer, Dataflow ingestion & retrieval pipelines.
• Use Terraform (IaC module development), GCP landing zones to design, provision, configure, migrate, and tune platform components using the required scope.
• Use IAM & secure pipelines to implement, harden, test, and remediate security and access controls using the required scope.
• Apply Tool orchestration & Function calling as additional skill requirements for this demand.
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Own technical design decisions, code and configuration reviews, and standards for the above tools.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Lead stakeholder alignment, prioritization, and cross-team dependency resolution.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 7 to 10 years of relevant industry experience aligned to the Senior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.
Skill Requirements
Agentic & AI
Agent Development Kit (ADK) / Vertex AI Agent Builder
Model Context Protocol (MCP) servers & clients
Tool orchestration & Function calling
Multimodal semantic extraction & inference
Graph & Retrieval
GraphRAG & Knowledge graphs
Vector embeddings & Hybrid search
Ontologies & Semantic schema mapping
PIM/PXM product data enrichment"
Secondary skills
"Data Foundations (GCP)
BigQuery lakehouse & context-aware data access
Cloud Composer / Dataflow ingestion & retrieval pipelines
Knowledge catalogs & AI data governance guardrails
Infrastructure & Deployment
Terraform (IaC module development)
GCP landing zones, IAM & secure pipelines"
TECHNICAL JOB DESCRIPTION
• Use Agent Development Kit (ADK), Vertex AI Agent Builder, Model Context Protocol (MCP) servers & clients, Multimodal semantic extraction & inference, GraphRAG & Knowledge graphs, Vector embeddings & Hy... to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope, supported by Knowledge catalogs & AI data governance guardrails.
• Use Ontologies & Semantic schema mapping, PIM/PXM product data enrichment to model, ingest, transform, secure, and serve data using the required scope, supported by BigQuery lakehouse & context-aware data access, Cloud Composer, Dataflow ingestion & retrieval pipelines.
• Use Terraform (IaC module development), GCP landing zones to design, provision, configure, migrate, and tune platform components using the required scope.
• Use IAM & secure pipelines to implement, harden, test, and remediate security and access controls using the required scope.
• Apply Tool orchestration & Function calling as additional skill requirements for this demand.
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Own technical design decisions, code and configuration reviews, and standards for the above tools.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Lead stakeholder alignment, prioritization, and cross-team dependency resolution.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 7 to 10 years of relevant industry experience aligned to the Senior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.
Other Requirements
TECHNICAL JOB DESCRIPTION
• Use Agent Development Kit (ADK), Vertex AI Agent Builder, Model Context Protocol (MCP) servers & clients, Multimodal semantic extraction & inference, GraphRAG & Knowledge graphs, Vector embeddings & Hy... to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope, supported by Knowledge catalogs & AI data governance guardrails.
• Use Ontologies & Semantic schema mapping, PIM/PXM product data enrichment to model, ingest, transform, secure, and serve data using the required scope, supported by BigQuery lakehouse & context-aware data access, Cloud Composer, Dataflow ingestion & retrieval pipelines.
• Use Terraform (IaC module development), GCP landing zones to design, provision, configure, migrate, and tune platform components using the required scope.
• Use IAM & secure pipelines to implement, harden, test, and remediate security and access controls using the required scope.
• Apply Tool orchestration & Function calling as additional skill requirements for this demand.
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Own technical design decisions, code and configuration reviews, and standards for the above tools.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Lead stakeholder alignment, prioritization, and cross-team dependency resolution.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 7 to 10 years of relevant industry experience aligned to the Senior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.