AI / ML Developer / Engineer

EXL; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

EXL Bengaluru seeks an AI Governance Engineer to configure and fine-tune EXLdata.ai agents, applying prompt engineering to optimize behavior and output quality. You will design governance workflows and data stewardship processes using AI agent orchestration.

Role involves documenting metadata, data lineage, and governance processes, and supporting dashboards for stewards and executives. Collaboration with GCP Engineers and Data Analysts is essential in sprint contexts.

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.

Responsibilities

• Configure and fine-tune AI agents 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 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.

Skills

EXLdata.ai Agents

Data Governance

Data Quality

Data Lineage

Stewardship Workbench

Vertex AI

BigQuery

GitHub Actions

Python

Nginx / Orchestrator

API gateway

GKE

Neo4j

Milvus

Knowledge Graph

Milvus Vector Database

Tools

Neo4j

Milvus

Knowledge Graph

GCP

Job description

• 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

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