ServiceNow Technical Architect — Conversational / GenAI

Position Description
ServiceNow Technical Architect – Conversational / GenAI
Location: Hyderabad, India
Experience: 6+ Years
Employment Type: Full-Time
Role: ServiceNow Technical Architect – Conversational AI / GenAI
Job Overview
We are looking for an experienced ServiceNow Technical Architect – Conversational / GenAI with 6+ years of experience to lead the architecture and implementation of enterprise conversational AI capabilities on the ServiceNow platform.
The role will own NLU model design, Virtual Agent architecture, conversational workflows, Now Assist/GenAI integration patterns, AI Agent capabilities, and enterprise AI guardrails.
The ideal candidate should have strong hands-on ServiceNow experience combined with an understanding of LLMs, prompt engineering, AI governance, human-in-the-loop controls, auditability, security, privacy, and responsible AI practices.
This role will work closely with ServiceNow engineering, Enterprise Architecture, Security, Privacy, Risk, and AI Governance teams to ensure that conversational and agentic AI solutions are scalable, secure, testable, auditable, and aligned with enterprise AI governance standards.
Key Responsibilities
Conversational Architecture
Own the architecture and technical design of ServiceNow Virtual Agent and conversational AI solutions.
Design and govern NLU intents, entities, utterances, conversation models, and conversational flows.
Define reusable architecture patterns for conversational experiences across multiple business functions.
Translate business requirements into scalable, testable, and governed conversational solutions.
Establish standards for conversational design, development, testing, deployment, and ongoing optimization.
Virtual Agent & NLU
Design and implement Virtual Agent topics, topic flows, NLU models, intents, entities, and conversation experiences.
Review and govern Virtual Agent topic design and implementation quality.
Optimize intent recognition, entity extraction, conversation completion, and resolution rates.
Define fallback and escalation mechanisms when conversational AI cannot confidently resolve a request.
Establish testing strategies for conversational accuracy, quality, and user experience.
GenAI / Now Assist Architecture
Design integration patterns for ServiceNow Now Assist and Generative AI capabilities.
Evaluate and implement LLM-based use cases within the ServiceNow ecosystem.
Define prompt engineering, prompt templates, context management, grounding, and response-generation patterns.
Design appropriate controls around AI-generated responses and AI-driven actions.
Ensure GenAI solutions are scalable, reliable, secure, and aligned with enterprise architecture principles.
AI Guardrails & Responsible AI
Design AI guardrails to control inappropriate, inaccurate, unsafe, or unauthorized AI-generated responses/actions.
Define human oversight and human-in-the-loop mechanisms for high-risk AI use cases.
Establish approval gates for AI-generated content and actions where required.
Design fallback, escalation, exception-handling, and intervention mechanisms.
Ensure AI solutions have appropriate controls around data access, privacy, security, and authorization.
Define risk-based controls based on the nature and impact of each AI use case.
Auditability & Governance
Ensure conversational and GenAI solutions maintain a clear audit trail.
Define logging and monitoring requirements for AI prompts, responses, actions, approvals, exceptions, and human interventions where applicable.
Ensure AI implementations align with enterprise AI governance, security, privacy, compliance, and risk-management requirements.
Participate in AI governance, architecture review, security, privacy, and risk review forums.
Provide technical input for AI use-case risk assessments and approval processes.
Analytics & Continuous Improvement
Own conversational analytics and define KPIs for conversational AI performance.
Monitor metrics such as:
Intent recognition accuracy
Containment/resolution rate
Fallback rate
Escalation rate
User satisfaction
AI response quality
Task completion rate
Analyze conversation failures and user feedback to continuously improve NLU models and conversation flows.
Establish continuous improvement processes for Virtual Agent and GenAI capabilities.
Agentic AI & Automation
Evaluate opportunities for agentic workflows and AI-driven automation within ServiceNow.
Design controlled AI agents capable of executing business actions within defined authorization boundaries.
Define approval, validation, and human intervention points for agentic workflows.
Ensure agentic solutions have measurable success criteria and appropriate risk controls.
Collaborate with platform, workflow, integration, and security teams to implement agentic solutions.
Stakeholder & Architecture Engagement
Represent the conversational AI squad in architecture, AI governance, security, privacy, and risk review forums.
Work closely with business stakeholders to understand use cases and translate them into technical solutions.
Partner with Enterprise Architecture, Cybersecurity, Data Privacy, Risk, and Compliance teams.
Provide technical leadership and architectural guidance to development teams.
Mentor developers and establish best practices for conversational and GenAI development.
Must-Have Skills & Experience
ServiceNow
6+ years of overall IT / ServiceNow experience.
Strong hands-on experience with ServiceNow Virtual Agent.
Hands-on experience with Virtual Agent Designer / NLU implementation.
Strong understanding of:
Virtual Agent topics
Topic flows
NLU intents
Entities
Utterances
Conversation design
Fallback and escalation flows
Experience designing and implementing conversational solutions on ServiceNow.
Strong understanding of ServiceNow platform architecture and integration capabilities.
GenAI / LLM
Practical understanding of Generative AI and Large Language Model (LLM) integration patterns.
Experience with prompt engineering / prompt design.
Understanding of:
Prompt templates
Context management
Grounding
Retrieval-based approaches
Response validation
Hallucination mitigation
AI response evaluation
Experience integrating or working with enterprise GenAI capabilities, preferably ServiceNow Now Assist.
Ability to translate business requirements into governed and testable AI/conversational solutions.
AI Governance & Risk
Strong understanding of enterprise AI governance and responsible AI principles.
Experience designing or working with:
Human-in-the-loop controls
Approval workflows
AI guardrails
Fallback mechanisms
AI auditability
Risk controls
AI-generated content validation
Understanding of security, privacy, compliance, and authorization considerations for AI solutions.
Ability to work with Security, Privacy, Risk, Compliance, and AI Governance stakeholders.
Experience supporting technical risk assessments and governance sign-offs.
Architecture & Stakeholder Management
Strong solution/technical architecture experience.
Ability to convert business use cases into scalable technical architecture.
Strong communication and stakeholder management skills.
Experience presenting architecture and technical decisions to senior stakeholders.
Ability to work effectively across engineering, architecture, security, business, and governance teams.
Good-to-Have Skills & Experience
ServiceNow AI
Hands-on experience with ServiceNow AI Agent Studio.
Experience with ServiceNow AI Agent Orchestrator.
Experience With Now Assist Capabilities Across ServiceNow Products.
Experience implementing AI-powered workflows using ServiceNow.
Experience with ServiceNow IntegrationHub, Flow Designer, and REST/SOAP integrations.
Agentic AI
Previous experience working on an agentic AI / AI-agent pilot or proof of concept.
Experience defining risk controls and success metrics for agentic workflows.
Understanding of AI agent concepts such as:
Tool calling
Agent orchestration
Planning and reasoning workflows
Autonomous vs. human-approved actions
Agent permissions and boundaries
Multi-step task execution
Experience designing human approval checkpoints for high-impact AI actions.
AI Engineering
Experience with LLM platforms such as Azure OpenAI, OpenAI, Google Gemini, or Amazon Bedrock.
Knowledge of RAG (Retrieval-Augmented Generation) architectures.
Understanding of vector databases and semantic search.
Experience with AI evaluation frameworks and response-quality measurement.
Knowledge of prompt injection, data leakage, hallucination, and other GenAI security risks.
ServiceNow Certifications
Preferred certifications include:
ServiceNow Certified System Administrator (CSA)
ServiceNow Certified Implementation Specialist – Virtual Agent
ServiceNow AI / GenAI-related certifications
ServiceNow Certified Application Developer (CAD)
Your future duties and responsibilities
Required Qualifications To Be Suc

Work arrangement
No