Senior Software Engineer

We are building a modern Workflow system with an AI-first experience layer. This role is for a hands-on product engineer who can ship full-stack capabilities end-to-end and treat AI as a core interaction model, not a bolt-on feature. You'll help deliver an AI-first front door workflow fulfilment experience, including AI-assisted workflows and agentic workflows that automate common operational tasks while maintaining stability, compliance, and auditability. Note: Prior ServiceNow experience is valued as domain context (ITSM patterns, SLAs, approvals, routing), but this is not a ServiceNow admin/config role.
The candidate will have responsibilities across the following functions:
Full Stack Product Delivery:
Build production-grade web experiences (portals, agent experiences, dashboards) and backend services (APIs, orchestration, data model).
Own features end-to-end: design/implementation, testing, deployment, monitoring, iteration.
AI First Feature Engineering (Core Expectation):
Deliver AI capabilities that materially improve service outcomes (e. g., smarter intake, better search, better knowledge interpretation, conversational service submission).
Implement and operate AI-assisted workflows and decisioning, including agentic workflows (with human-in-the-loop checkpoints where needed).
Build AI components with evaluation discipline (quality checks, regression testing, monitoring) and explicit safety/operational controls.
Reliable Workflow and Data Foundations:
Design lifecycle state models, routing, approvals, SLAs, and auditability for service management entities.
Engineer for resilience and measurable performance (latency targets, stability, avoidance of regressions to operational processes).
Security, Privacy, and Governance by Design:
Ensure AI experiences respect access controls and data boundaries (permissions-based responses, safe tool usage).
Partner with security/compliance stakeholders to implement guardrails (data leakage prevention, prompt injection resilience, auditability).
Collaboration and Technical Leadership:
Work closely with product, UX, platform/SRE, and service operations stakeholders.
Provide technical leadership through design reviews, mentoring, and high engineering standards.
Expectations:
AI-first front door: conversational entry points (Teams/web), smart search, guided self-service, and AI-assisted intake that reduces friction and drives deflection.
Agentic workflows (controlled autonomy): AI-assisted decisioning and multi-step orchestration for repeatable operations (triage, routing, knowledge capture, change risk checks) with strong guardrails.
Workflow orchestration foundation: reliable workflow definition/execution.
Search + knowledge intelligence: better retrieval and intent-based search experiences to improve self-service and reduce tickets.
Enterprise-ready integration and compliance: identity, asset/service context, audit trails, latency and stability targets appropriate for service operations.
Requirements:
6+ years building production systems as a full-stack engineer (React/Angular/Vue + Node/Java/. NET/Python + SQL/NoSQL).
Strong API design, integration patterns, and production operability (logging/metrics/tracing).
Experience building workflow-heavy products (forms, state transitions, queues, policy/routing).
Working knowledge of modern engineering practices: Git, CI/CD, testing, secure coding.
Experience working with DBs- PostgreSQL.
Good to have ServiceNow, Cloud Experience: Azure/ GCP.
Preferred Qualifications:
Demonstrated experience shipping AI-powered features in production or strong evidence of building LLM-enabled systems (RAG/search, tool use, orchestration, evaluation/monitoring, safe deployment practices).
Ability to translate service management needs into AI-supported workflows (e. g., conversational interface, knowledge interpretation, deflection).
Experience with Temporal or comparable workflow orchestration tools for building and managing long-running, distributed, event-driven workflows.
Past or present ServiceNow exposure to understand service management patterns and workflows.
Experience with distributed systems, asynchronous processing, queues/events.
Strong product engineering mindset: experimentation, metrics, user journeys, incremental delivery.
Experience modernising or replacing enterprise platforms (including SaaS/vendor transitions).

Experience
6-10 yrs