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**Job Description: 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 Engi