Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : AI Agents & Workflow Integration

Good to have skills : Virtual Agents, Generative AI

Minimum 7.5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

As a Custom Software Engineer, a typical day involves designing, coding, and improving various components within systems or applications to meet unique business requirements. The role includes working with modern development frameworks and following agile methodologies to ensure the delivery of scalable and efficient software solutions. Collaboration with different teams and continuous enhancement of software components are integral parts of the daily workflow, focusing on creating tailored solutions that align with organizational goals and client expectations.

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.