Posted 22 August, 2026
AI Agents & Workflow Integration
NR Consulting
Bangalore,Karnataka
Full Time
Reference: 365_463738_26-23628
Title: AI Agents & Workflow Integration
Location: Bangalore
Exp: 7+ Years
Job Description:
Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead the implementation of best practices to improve software development processes and team productivity.
- Mentor junior team members to support their professional growth and skill development.
- Coordinate cross-functional efforts to ensure alignment of project objectives and timely delivery.
- Design and build the Agent Orchestration Service for Akura.
- Integrate AI/rule-based agents with Kafka-based event flows.
- Consume events from Kafka topics such as: guidewire.claim.event.created, incident.evaluation.requested, agent.incident.decision.created, incident.creation.requested, audit.event.recorded
- Invoke the appropriate AI agent, rule engine, or decision workflow based on the event type.
- Publish structured agent decision events back to Kafka for downstream services.
- Ensure agent decisions are consumed by ServiceNow Connector, Audit Service, and APEX UI.
- Build or integrate the ServiceNow incident triage agent for Akura.
- Evaluate Guidewire claim/system events and determine whether an incident should be created, updated, ignored, or routed for human review.
- Generate structured recommendations including: Incident required / not required, Severity, Assignment group, Probable classification, Duplicate incident indicator, Recommended next action, Human approval requirement
- Support incident triage workflows aligned to ServiceNow integration needs.
- Build context enrichment logic before invoking the agent.
- Retrieve relevant context from: Guidewire APIs/events, PostgreSQL platform data, ServiceNow incident history, Runbooks and known-error library, Audit/event history, Observability logs and alerts
- Prepare structured context packets for the agent.
- Implement Retrieval-Augmented Generation patterns where knowledge base or runbook context is required.
- Ensure the agent does not rely only on raw Kafka payloads for decisions.
- Define and implement structured agent decision payloads.
- Ensure all agent outputs are machine-readable and auditable.
- Include mandatory metadata such as: Event ID, Correlation ID, Agent name and version, Source event reference, Decision, Confidence score, Reason summary, Recommended action, Human approval flag, Timestamp
- Work with the Schema Governance Engineer to align decision events with schema standards.
- Ensure downstream services do not parse free-form AI text for critical decisions.
- Implement guardrails around agent behavior and tool execution.
- Ensure agent decisions follow defined business rules, approval policies, and risk controls.
- Support decision modes such as: Auto-create incident, Recommend for user approval, No action / audit only
- Build human-in-the-loop approval routing for medium-risk or low-confidence decisions.
- Prevent direct uncontrolled agent execution against enterprise systems.
- Ensure action execution is routed through governed services such as ServiceNow Connector rather than direct unmanaged agent calls.
- Integrate the agent with approved tool APIs and backend services.
- Support tool calls through controlled service layers for: Guidewire context lookup, ServiceNow incident search/create/update, Audit logging, Notification generation, Runbook retrieval, Observability lookup
- Ensure each tool invocation is authorized, logged, validated, and traceable.
- Work with Backend and DevOps teams to secure credentials, secrets, and API access.
- Ensure every agent invocation is traceable from source event to final action.
- Store agent input, context reference, decision output, confidence score, rule result, and action outcome.
- Integrate with append-only audit tables and object evidence storage.
- Ensure APEX UI can display event status, agent recommendation, incident outcome, and audit trail.
- Support replay and investigation of historical agent decisions.
- Instrument agent services with logs, metrics, traces, health checks, and correlation IDs.
- Work with Observability Platform Engineer to expose: Agent success/failure rate, Decision confidence distribution, Processing latency, Failed tool calls, Retry/DLQ counts, Human approval queue volume
- Support OpenTelemetry integration across the agent orchestration flow.
- Support production readiness reviews, runbooks, and handover documentation.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in AI Agents & Workflow Integration.
- Good To Have Skills: Experience with Virtual Agents, Generative AI.
- Strong knowledge of software development lifecycle and agile methodologies.
- Ability to design and integrate complex workflows within software systems.
- Experience in troubleshooting and optimizing AI-driven software components.
- Familiarity with modern programming languages and frameworks relevant to AI and workflow automation.
- Hands-on experience in Python, Java, Spring Boot, FastAPI, or equivalent backend technology.
- Experience integrating AI/LLM services, AI agents, or rule-based decision engines.
- Experience with REST API integration and microservice-based architecture.
- Understanding of Kafka-based event-driven architecture.
- Ability to consume and publish structured events through Kafka.
- Experience with prompt design, context preparation, structured outputs, and safe AI execution patterns.
- Understanding of RAG/context enrichment patterns.
- Experience working with JSON-based event contracts and API payloads.
- Good understanding of authentication, authorization, secrets, and secure API calls.
- Strong debugging and production support mindset.
- Ability to work with Solution Architects and backend teams to translate agent workflows into deployable services.
- Experience with Amazon MSK / Apache Kafka.
- Experience with Kafka Streams or event processing.
- Experience with ServiceNow incident management APIs.
- Guidewire Cloud or insurance operations exposure.
- Experience with runbook automation, incident triage, root cause analysis, or operational automation.
- Experience with LangGraph, Semantic Kernel, AutoGen, Amazon Bedrock Agents, Azure AI Agent Service, OpenAI tool/function calling, or equivalent agent frameworks.
- Experience with vector databases or PostgreSQL/pgvector.
- Experience with OpenTelemetry, CloudWatch, Grafana, or similar observability tooling.
- Experience with GitHub Actions, Docker, EKS/ECS, Terraform, or Helm.
Additional Information:
- The candidate should have minimum 7.5 years of experience in AI Agents & Workflow Integration.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
Location: Bangalore
Exp: 7+ Years
Job Description:
Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead the implementation of best practices to improve software development processes and team productivity.
- Mentor junior team members to support their professional growth and skill development.
- Coordinate cross-functional efforts to ensure alignment of project objectives and timely delivery.
- Design and build the Agent Orchestration Service for Akura.
- Integrate AI/rule-based agents with Kafka-based event flows.
- Consume events from Kafka topics such as: guidewire.claim.event.created, incident.evaluation.requested, agent.incident.decision.created, incident.creation.requested, audit.event.recorded
- Invoke the appropriate AI agent, rule engine, or decision workflow based on the event type.
- Publish structured agent decision events back to Kafka for downstream services.
- Ensure agent decisions are consumed by ServiceNow Connector, Audit Service, and APEX UI.
- Build or integrate the ServiceNow incident triage agent for Akura.
- Evaluate Guidewire claim/system events and determine whether an incident should be created, updated, ignored, or routed for human review.
- Generate structured recommendations including: Incident required / not required, Severity, Assignment group, Probable classification, Duplicate incident indicator, Recommended next action, Human approval requirement
- Support incident triage workflows aligned to ServiceNow integration needs.
- Build context enrichment logic before invoking the agent.
- Retrieve relevant context from: Guidewire APIs/events, PostgreSQL platform data, ServiceNow incident history, Runbooks and known-error library, Audit/event history, Observability logs and alerts
- Prepare structured context packets for the agent.
- Implement Retrieval-Augmented Generation patterns where knowledge base or runbook context is required.
- Ensure the agent does not rely only on raw Kafka payloads for decisions.
- Define and implement structured agent decision payloads.
- Ensure all agent outputs are machine-readable and auditable.
- Include mandatory metadata such as: Event ID, Correlation ID, Agent name and version, Source event reference, Decision, Confidence score, Reason summary, Recommended action, Human approval flag, Timestamp
- Work with the Schema Governance Engineer to align decision events with schema standards.
- Ensure downstream services do not parse free-form AI text for critical decisions.
- Implement guardrails around agent behavior and tool execution.
- Ensure agent decisions follow defined business rules, approval policies, and risk controls.
- Support decision modes such as: Auto-create incident, Recommend for user approval, No action / audit only
- Build human-in-the-loop approval routing for medium-risk or low-confidence decisions.
- Prevent direct uncontrolled agent execution against enterprise systems.
- Ensure action execution is routed through governed services such as ServiceNow Connector rather than direct unmanaged agent calls.
- Integrate the agent with approved tool APIs and backend services.
- Support tool calls through controlled service layers for: Guidewire context lookup, ServiceNow incident search/create/update, Audit logging, Notification generation, Runbook retrieval, Observability lookup
- Ensure each tool invocation is authorized, logged, validated, and traceable.
- Work with Backend and DevOps teams to secure credentials, secrets, and API access.
- Ensure every agent invocation is traceable from source event to final action.
- Store agent input, context reference, decision output, confidence score, rule result, and action outcome.
- Integrate with append-only audit tables and object evidence storage.
- Ensure APEX UI can display event status, agent recommendation, incident outcome, and audit trail.
- Support replay and investigation of historical agent decisions.
- Instrument agent services with logs, metrics, traces, health checks, and correlation IDs.
- Work with Observability Platform Engineer to expose: Agent success/failure rate, Decision confidence distribution, Processing latency, Failed tool calls, Retry/DLQ counts, Human approval queue volume
- Support OpenTelemetry integration across the agent orchestration flow.
- Support production readiness reviews, runbooks, and handover documentation.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in AI Agents & Workflow Integration.
- Good To Have Skills: Experience with Virtual Agents, Generative AI.
- Strong knowledge of software development lifecycle and agile methodologies.
- Ability to design and integrate complex workflows within software systems.
- Experience in troubleshooting and optimizing AI-driven software components.
- Familiarity with modern programming languages and frameworks relevant to AI and workflow automation.
- Hands-on experience in Python, Java, Spring Boot, FastAPI, or equivalent backend technology.
- Experience integrating AI/LLM services, AI agents, or rule-based decision engines.
- Experience with REST API integration and microservice-based architecture.
- Understanding of Kafka-based event-driven architecture.
- Ability to consume and publish structured events through Kafka.
- Experience with prompt design, context preparation, structured outputs, and safe AI execution patterns.
- Understanding of RAG/context enrichment patterns.
- Experience working with JSON-based event contracts and API payloads.
- Good understanding of authentication, authorization, secrets, and secure API calls.
- Strong debugging and production support mindset.
- Ability to work with Solution Architects and backend teams to translate agent workflows into deployable services.
- Experience with Amazon MSK / Apache Kafka.
- Experience with Kafka Streams or event processing.
- Experience with ServiceNow incident management APIs.
- Guidewire Cloud or insurance operations exposure.
- Experience with runbook automation, incident triage, root cause analysis, or operational automation.
- Experience with LangGraph, Semantic Kernel, AutoGen, Amazon Bedrock Agents, Azure AI Agent Service, OpenAI tool/function calling, or equivalent agent frameworks.
- Experience with vector databases or PostgreSQL/pgvector.
- Experience with OpenTelemetry, CloudWatch, Grafana, or similar observability tooling.
- Experience with GitHub Actions, Docker, EKS/ECS, Terraform, or Helm.
Additional Information:
- The candidate should have minimum 7.5 years of experience in AI Agents & Workflow Integration.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
