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AI Native Software Engineer

Accenture · Bengaluru, India

About this role

Accenture seeks an AI Native Software Engineer in Bengaluru for a full-time role developing production-ready, AI-enabled software on ServiceNow. The position emphasizes AI-native development and validation practices, software quality, compliance, and continuous improvement of how solutions are built and operated.

Responsibilities

  • Develop ServiceNow AI features using Now Assist, Virtual Agent, AI Search, App Engine Studio, Flow Designer, and IntegrationHub.
  • Implement agentic patterns for workflow automation and developer assistance. Write prompts and evaluators, and contribute to retrieval-augmented generation (RAG) strategies and testing frameworks.
  • Work with architects and product owners in agile pods, participating in sprints and code reviews. Apply Responsible AI principles and secure engineering practices.

Qualifications and skills:

  • ServiceNow is the required skill. The posting specifies a minimum of 3 years of experience; its job summary lists 2–5 years. It also requires 15 years of full-time education.
  • Strong JavaScript, REST API, and ServiceNow platform development fundamentals; familiarity with ServiceNow App Engine, Flow Designer, IntegrationHub, and Scoped Applications.
  • Understanding of large language models, prompt engineering, and evaluation metrics; knowledge of Virtual Agent, AI Search tuning, and Now Assist configuration. Exposure to ServiceNow data models, UI policies, Business Rules, and client scripts; awareness of SOAP/REST integration, MID Server, OAuth, and SAML; and basic understanding of RAG, vector search, and orchestration frameworks.
  • Collaboration, communication, problem-solving, attention to detail, adaptability, and a continuous-learning mindset are sought.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

ServiceNowJavaScriptREST APIsNow AssistVirtual AgentAI SearchApp Engine StudioFlow DesignerIntegrationHubScoped ApplicationsLarge Language ModelsPrompt EngineeringAI EvaluationRAGVector SearchWorkflow AutomationResponsible AISecure EngineeringServiceNow Data ModelsUI PoliciesBusiness RulesClient ScriptsSOAPMID ServerOAuthSAMLAgileCode ReviewCommunicationProblem Solving

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Get interview-ready for this role

A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Ship ServiceNow AI features

    The role calls for AI-enabled features using Now Assist, Virtual Agent, and AI Search, built with App Engine Studio, Flow Designer, and IntegrationHub. ServiceNow is the stated must-have skill.

  • Develop and validate AI-native workflows

    Responsibilities include agentic patterns for workflow automation and developer assistance, authoring prompts and evaluators, and contributing to RAG strategies and testing frameworks.

  • Maintain production quality and safeguards

    The role description emphasizes production-ready software, quality, and compliance. The responsibilities specify Responsible AI principles and secure engineering practices.

  • Deliver with the agile pod

    The engineer works with architects and product owners in sprints and code reviews, with continuous improvement to how solutions are built and operated.

Likely challenges to think through

  • Automation versus dependable AI output

    Preparation hypothesis: Agentic workflows may automate useful work while producing outputs that need validation. Prepare to explain how prompts, evaluators, and tests could help assess an AI-enabled workflow before release.

  • Integration flexibility versus security

    Preparation hypothesis: Connecting ServiceNow workflows to other systems can add capability but complicate data access and authentication. Review how REST integrations, IntegrationHub, and the listed OAuth and SAML concepts relate to secure design.

  • Iteration speed versus review rigor

    Preparation hypothesis: Agile delivery may create tension between quick changes and the stated quality, compliance, and code-review expectations. Prepare an example of how to validate a change and communicate its trade-offs during a sprint.

03

Practice your answers

Technical practice

Suggested practice: How would you decide between a Business Rule, client script, and UI policy for ServiceNow behavior?

What to coverThe posting calls for exposure to these platform mechanisms and strong JavaScript fundamentals. Explain where each runs, what it can enforce, and how you would test the behavior without relying on client-side checks for server-side validation.

Suggested practice: How would you structure an AI-enabled ServiceNow application in App Engine Studio?

What to coverThe posting names App Engine Studio, Scoped Applications, and ServiceNow data models. Discuss application boundaries, data access, maintainability, and what you would verify before shipping.

Suggested practice: How would you automate a workflow that calls an external service?

What to coverThe role names Flow Designer, IntegrationHub, REST APIs, and awareness of SOAP, MID Server, OAuth, and SAML. As preparation, describe when those integration concepts matter and how you would handle failures, credentials, and testing.

Suggested practice: How would you configure and validate a Now Assist feature?

What to coverThe posting explicitly names Now Assist configuration and AI-enabled features on ServiceNow. Discuss the intended user task, configuration choices, evaluation against representative cases, and safeguards before production use.

Suggested practice: How would you design a Virtual Agent interaction for a service request?

What to coverVirtual Agent is named in the responsibilities and skills. As preparation, explain how you would define the conversation's scope, connect it to an appropriate workflow, and check that users can recover when the interaction fails.

Suggested practice: How would you tune and evaluate AI Search?

What to coverThe posting specifically calls for knowledge of AI Search tuning. Discuss relevance testing with representative queries, how you would investigate poor results, and the trade-off between finding more results and finding the right ones.

Suggested practice: Where would an agentic pattern help workflow automation or developer assistance?

What to coverImplementing agentic patterns for both uses is a stated responsibility. As preparation, describe a bounded task, the actions an agent could take, and where validation or human control should limit those actions.

Suggested practice: How would you write and evaluate prompts for a ServiceNow AI feature?

What to coverThe role includes authoring prompts and evaluators and understanding LLM evaluation metrics. Explain how you would specify the task, assemble representative test cases, choose useful measures, and investigate inconsistent or incorrect outputs.

Suggested practice: How would you assess whether RAG would improve an AI feature?

What to coverThe posting asks for contributions to RAG strategies and a basic understanding of vector search and orchestration frameworks. As preparation, explain retrieval, grounding, and how you would compare answer quality and failure modes with and without retrieved context.

Suggested practice: What checks would you apply before shipping an AI-enabled feature?

What to coverThe role emphasizes production readiness, testing frameworks, Responsible AI, secure engineering, quality, and compliance. Discuss practical validation of outputs and workflow behavior, access to data, and how findings would feed into improvements after release.

Behavioural practice

Suggested practice: Tell me about collaborating with different roles to deliver a technical change.

What to coverThe posting describes agile pods with architects and product owners. Use a real situation, the actions you took to align decisions or clarify requirements, and the result.

Suggested practice: Tell me about giving or receiving consequential code-review feedback.

What to coverParticipation in code reviews is a stated responsibility. Describe the situation, how you communicated and acted on the feedback, and its effect on quality or team progress.

Suggested practice: Tell me about diagnosing a difficult software defect.

What to coverThe posting seeks problem-solving and attention to detail. Give a real example covering the symptoms, the steps you took to isolate and verify the cause, and the outcome.

Suggested practice: Tell me about adapting when priorities changed during delivery.

What to coverThe role calls for adaptability in a fast-paced, client-focused environment and participation in sprints. Explain the situation, how you reprioritized or communicated trade-offs, and the result.

Suggested practice: Tell me about learning an unfamiliar technology to improve your work.

What to coverCuriosity and continuous learning are explicitly listed as soft skills. Describe a real learning need, what you did to build and apply your understanding, and the observable result.

02

Sharpen your knowledge

Topics to prepare

  • ServiceNow platform fundamentals

    Posting: ServiceNow is the required skill; it also names Scoped Applications, data models, UI policies, Business Rules, and client scripts. Suggested exercise: draw a scoped-app design and explain where each of those elements would handle data, validation, or user interaction.

  • ServiceNow AI feature choices

    Posting: The role develops features with Now Assist, Virtual Agent, and AI Search. Suggested exercise: for three example requests—a conversational task, a search query, and an assisted response—explain which feature you would consider and what you would validate.

  • LLMs, RAG, and evaluation

    Posting: LLMs, prompt engineering, evaluation metrics, RAG, vector search, and orchestration frameworks are named at varying levels of depth. Suggested exercise: sketch a retrieval-to-answer flow and define tests for answer relevance, grounding, and failure cases.

  • Agentic workflow patterns

    Posting: Agentic patterns are used for workflow automation and developer assistance. Suggested exercise: diagram a hypothetical multi-step workflow, including the action boundaries, checks, and points where a person should review the result.

  • Integrations and authentication

    Posting: REST APIs are a strong fundamental; SOAP/REST patterns, MID Server, OAuth, and SAML require awareness. Suggested exercise: explain an example ServiceNow-to-external-system request, distinguishing the integration method from authentication and identifying likely failure points.

  • Quality, security, and delivery

    Posting: The role calls for production-ready software, Responsible AI, secure engineering, testing, sprints, and code reviews. Suggested exercise: prepare a review checklist covering functional tests, AI-output risks, access controls, and maintainability for a hypothetical feature.

Skills to revise

  • Write and review ServiceNow JavaScript

    Posting: Strong JavaScript and ServiceNow development fundamentals are specified. Suggested exercise: write a small hypothetical Business Rule or client script, then review its trigger, data handling, error cases, and readability.

  • Build a scoped workflow

    Posting: App Engine Studio, Flow Designer, and IntegrationHub are named for AI-enabled development. Suggested exercise: in a practice environment if available, outline or build a scoped request workflow with a trigger, decision, and integration step; explain how you would test each.

  • Configure and test AI experiences

    Posting: Now Assist configuration, Virtual Agent, and AI Search tuning are named. Suggested exercise: devise sample user queries and expected outcomes for each, then describe a configuration or tuning change you would try when an outcome fails.

  • Implement a REST integration

    Posting: REST APIs and IntegrationHub are relevant to the work. Suggested exercise: draft a request and response contract for a hypothetical integration, including authentication handling, error responses, and a test for failed calls.

  • Author prompts and evaluators

    Posting: The responsibilities explicitly include prompts, evaluators, RAG strategies, and testing frameworks. Suggested exercise: write a prompt for an AI-assisted ServiceNow task and a small set of input, expected-behavior, and failure-case tests; explain how you would score the results.

  • Practice a code-review walkthrough

    Posting: The engineer participates in agile sprints and code reviews with architects and product owners. Suggested exercise: present a hypothetical change in a brief review, covering its purpose, tests, security considerations, and one trade-off requiring product input.

04

Your preparation checklist

  • Assemble a ServiceNow evidence sheet

    List specific work or study examples involving ServiceNow development, JavaScript, and REST APIs, with your contribution and result for each. The posting states a minimum of 3 years of experience and 15 years of full-time education; have accurate dates ready to discuss.

  • Prepare an AI feature walkthrough

    Choose a real project, if available, and explain the problem, your implementation, and how you validated it. Connect only the tools you actually used to the posting’s Now Assist, Virtual Agent, AI Search, App Engine Studio, Flow Designer, and IntegrationHub responsibilities.

  • Sketch a ServiceNow workflow design

    As interview practice, diagram a hypothetical AI-assisted workflow: its data model, Scoped Application boundary, Flow Designer steps, and integration points. Note where Business Rules, client scripts, or UI policies would be appropriate and why.

  • Draft a prompt and evaluation example

    Prepare a sample prompt, an evaluator, a small test set, and metrics for an AI-enabled feature. Be ready to explain failure cases and, where relevant, how a RAG approach could be tested; the posting names prompts, evaluators, RAG, and testing frameworks.

  • Map integration and safety decisions

    Create a short design note covering REST or SOAP integration choices, authentication considerations such as OAuth or SAML, and when a MID Server might matter. Add concrete checks for secure engineering, Responsible AI, quality, and compliance.

  • Rehearse a collaboration example

    Prepare one concise account of working with architects or product owners, handling sprint feedback, and improving code through review. State your own actions and the outcome without implying that Accenture uses a particular process beyond the agile pods, sprints, and code reviews in the posting.

  • Write role-specific questions

    Bring questions about which ServiceNow AI capabilities the team is building, how prompts and evaluators are tested, and how architects and product owners balance delivery with Responsible AI and security requirements.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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