We are seeking skilled AI/ML Developers/Engineers to support the configuration and deployment of EXLdata.ai™ Agentic Data Governance agents for a leading P&C insurance client. You will configure AI agents, automate governance workflows, and support the analysis and documentation of metadata, data lineage, and governance processes across Claims and Underwriting domains Key Responsibilities: - Configure and fine-tune AI agents (Data Governance, Data Quality, Lineage, Stewardship) on the EXLdata.ai™ platform - Apply prompt engineering techniques to optimize agent behavior, accuracy, and output quality - Design and automate governance workflows and data stewardship processes using AI agent orchestration - Perform current-state analysis and document metadata, data lineage, and governance processes - Support configuration of governance workflows and reporting dashboards for stewards and executives - Integrate AI agents with backend systems, Knowledge Graph (Neo4j), and Vector Database (Milvus) - Collaborate with GCP Engineers, Solution Architects, and Data Analysts to deliver sprint objectives - Participate in Agile ceremonies — daily standups, sprint demos, and retrospectives - Troubleshoot agent performance, data pipeline issues, and workflow errors in the GKE environment Qualifications: - 3+ years of experience in AI/ML development, agent configuration, or LLM-based application development - Strong expertise in prompt engineering and AI workflow automation - Hands-on experience with AI agent frameworks and orchestration tools - Knowledge of data governance concepts: data quality, stewardship, lineage, MDM/RDM, and metadata management - Familiarity with governance agents: Data Quality (DQ), Stewardship, MDM/RDM agents - Experience working with REST APIs and event-driven integration - Proficiency in Python for scripting, automation, and data processing - Experience with CI/CD pipelines using GitHub / GitHub Actions - Strong analytical skills to document and assess current-state data and governance processes Preferred Skills - Experience in the insurance domain (Claims, Underwriting, or Policy data) - Familiarity with EXLdata.ai™ platform or similar agentic data intelligence platforms - GCP Professional certification (ML Engineer, Data Engineer, or Cloud Developer) - Experience with offshore/onshore hybrid Agile delivery models Skills & Experience The following tools are part of the EXLdata.ai™ GCP architecture. Familiarity is an advantage — not all are mandatory. Training and ramp-up support will be provided. Must-Have Skills & Experience | EXLdata.ai™ Agents | Data Governance, Data Quality, Data Lineage, Stewardship Workbench agents | | --- | --- | | Vertex AI (GCP) | Google AI/ML platform for model serving and agent inference | | BigQuery | Managed analytics data warehouse for querying governance data | | GitHub / Git + Actions | Source control and CI/CD for agent configuration and deployment | | Python | Primary language for agent scripting and workflow automation | | Nginx / Orchestrator | API gateway and agent orchestration layer within GKE | Preferred — Nice to Have | GKE (Google Kubernetes Engine) | Container orchestration platform hosting EXLdata.ai™ agents | | --- | --- | | Neo4j Graph Database | Knowledge graph for entity relationships and data lineage | | Milvus Vector Database | Vector DB for semantic search and embedding storage (open-source) | | Cloud SQL | Managed relational DB for metadata storage | | Google Secret Manager (CSI) | Secrets management via CSI Secret Store integration in GKE | | Google Filestore | Persistent shared storage (RWX, CSI-backed PVC) | | Guidewire APIs / Events | Insurance platform integration for Claims & Underwriting data | | Okta | Identity access management and access scoping via VPC rules | Awareness Level — Environment Context | Cloud Logging / gCloud CLI | Operational logging and CLI access for environment support | | --- | --- | | IAM (Identity & Access Mgmt) | GCP role-based access control and service account management | | Cloud KMS / Secrets Manager | Key management and secret storage for secure deployments | | Artifact Registry | Container image registry for agent Docker images | | Cloud DNS | DNS routing for subdomain-based service access | | Backup & DR Service | Disaster recovery and backup for platform resilience | ### Responsibilities Key Responsibilities: - Configure and fine-tune AI agents (Data Governance, Data Quality, Lineage, Stewardship) on the EXLdata.ai™ platform - Apply prompt engineering techniques to optimize agent behavior, accuracy, and output quality - Design and automate governance workflows and data stewardship processes using AI agent orchestration - Perform current-state analysis and document metadata, data lineage, and governance processes - Support configuration of governance workflows and reporting dashboards for stewards and executives - Integrate AI agents with backend systems, Knowledge Graph (Neo4j), and Vector Database (Milvus) - Collaborate with GCP Engineers, Solution Architects, and Data Analysts to deliver sprint objectives - Participate in Agile ceremonies — daily standups, sprint demos, and retrospectives - Troubleshoot agent performance, data pipeline issues, and workflow errors in the GKE environment Qualifications: - 3+ years of experience in AI/ML development, agent configuration, or LLM-based application development - Strong expertise in prompt engineering and AI workflow automation - Hands-on experience with AI agent frameworks and orchestration tools - Knowledge of data governance concepts: data quality, stewardship, lineage, MDM/RDM, and metadata management - Familiarity with governance agents: Data Quality (DQ), Stewardship, MDM/RDM agents - Experience working with REST APIs and event-driven integration - Proficiency in Python for scripting, automation, and data processing - Experience with CI/CD pipelines using GitHub / GitHub Actions - Strong analytical skills to document and assess current-state data and governance processes Preferred Skills - Experience in the insurance domain (Claims, Underwriting, or Policy data) - Familiarity with EXLdata.ai™ platform or similar agentic data intelligence platforms - GCP Professional certification (ML Engineer, Data Engineer, or Cloud Developer) - Experience with offshore/onshore hybrid Agile delivery models Skills & Experience The following tools are part of the EXLdata.ai™ GCP architecture. Familiarity is an advantage — not all are mandatory. Training and ramp-up support will be provided. Must-Have Skills & Experience | EXLdata.ai™ Agents | Data Governance, Data Quality, Data Lineage, Stewardship Workbench agents | | --- | --- | | Vertex AI (GCP) | Google AI/ML platform for model serving and agent inference | | BigQuery | Managed analytics data warehouse for querying governance data | | GitHub / Git + Actions | Source control and CI/CD for agent configuration and deployment | | Python | Primary language for agent scripting and workflow automation | | Nginx / Orchestrator | API gateway and agent orchestration layer within GKE | Preferred — Nice to Have | GKE (Google Kubernetes Engine) | Container orchestration platform hosting EXLdata.ai™ agents | | --- | --- | | Neo4j Graph Database | Knowledge graph for entity relationships and data lineage | | Milvus Vector Database | Vector DB for semantic search and embedding storage (open-source) | | Cloud SQL | Managed relational DB for metadata storage | | Google Secret Manager (CSI) | Secrets management via CSI Secret Store integration in GKE | | Google Filestore | Persistent shared storage (RWX, CSI-backed PVC) | | Guidewire APIs / Events | Insurance platform integration for Claims & Underwriting data | | Okta | Identity access management and access scoping via VPC rules | Awareness Level — Environment Context | Cloud Logging / gCloud CLI | Operational logging and CLI access for environment support | | --- | --- | | IAM (Identity & Access Mgmt) | GCP role-based access control and service account management | | Cloud KMS / Secrets Manager | Key management and secret storage for secure deployments | | Artifact Registry | Container image registry for agent Docker images | | Cloud DNS | DNS routing for subdomain-based service access | | Backup & DR Service | Disaster recovery and backup for platform resilience | ### Qualifications Key Responsibilities: - Configure and fine-tune AI agents (Data Governance, Data Quality, Lineage, Stewardship) on the EXLdata.ai™ platform - Apply prompt engineering techniques to optimize agent behavior, accuracy, and output quality - Design and automate governance workflows and data stewardship processes using AI agent orchestration - Perform current-state analysis and document metadata, data lineage, and governance processes - Support configuration of governance workflows and reporting dashboards for stewards and executives - Integrate AI agents with backend systems, Knowledge Graph (Neo4j), and Vector Database (Milvus) - Collaborate with GCP Engineers, Solution Architects, and Data Analysts to deliver sprint objectives - Participate in Agile ceremonies — daily standups, sprint demos, and retrospectives - Troubleshoot agent performance, data pipeline issues, and workflow errors in the GKE environment Qualifications: - 3+ years of experience in AI/ML development, agent configuration, or LLM-based application development - Strong expertise in prompt engineering and AI workflow automation - Hands-on experience with AI agent frameworks and orchestration tools - Knowledge of data governance concepts: data quality, stewardship, lineage, MDM/RDM, and metadata management - Familiarity with governance agents: Data Quality (DQ), Stewardship, MDM/RDM agents - Experience working with REST APIs and event-driven integration - Proficiency in Python for scripting, automation, and data processing - Experience with CI/CD pipelines using GitHub / GitHub Actions - Strong analytical skills to document and assess current-state data and governance processes Preferred Skills - Experience in the insurance domain (Claims, Underwriting, or Policy data) - Familiarity with EXLdata.ai™ platform or similar agentic data intelligence platforms - GCP Professional certification (ML Engineer, Data Engineer, or Cloud Developer) - Experience with offshore/onshore hybrid Agile delivery models Skills & Experience The following tools are part of the EXLdata.ai™ GCP architecture. Familiarity is an advantage — not all are mandatory. Training and ramp-up support will be provided. Must-Have Skills & Experience | EXLdata.ai™ Agents | Data Governance, Data Quality, Data Lineage, Stewardship Workbench agents | | --- | --- | | Vertex AI (GCP) | Google AI/ML platform for model serving and agent inference | | BigQuery | Managed analytics data warehouse for querying governance data | | GitHub / Git + Actions | Source control and CI/CD for agent configuration and deployment | | Python | Primary language for agent scripting and workflow automation | | Nginx / Orchestrator | API gateway and agent orchestration layer within GKE | Preferred — Nice to Have | GKE (Google Kubernetes Engine) | Container orchestration platform hosting EXLdata.ai™ agents | | --- | --- | | Neo4j Graph Database | Knowledge graph for entity relationships and data lineage | | Milvus Vector Database | Vector DB for semantic search and embedding storage (open-source) | | Cloud SQL | Managed relational DB for metadata storage | | Google Secret Manager (CSI) | Secrets management via CSI Secret Store integration in GKE | | Google Filestore | Persistent shared storage (RWX, CSI-backed PVC) | | Guidewire APIs / Events | Insurance platform integration for Claims & Underwriting data | | Okta | Identity access management and access scoping via VPC rules | Awareness Level — Environment Context | Cloud Logging / gCloud CLI | Operational logging and CLI access for environment support | | --- | --- | | IAM (Identity & Access Mgmt) | GCP role-based access control and service account management | | Cloud KMS / Secrets Manager | Key management and secret storage for secure deployments | | Artifact Registry | Container image registry for agent Docker images | | Cloud DNS | DNS routing for subdomain-based service access | | Backup & DR Service | Disaster recovery and backup for platform resilience |