New opportunity

AI Native Software Engineer

Accenture · Bengaluru, India

About this role

Accenture seeks an AI Native Software Engineer in Bengaluru to build and ship production-ready software with AI integrated into the engineering lifecycle. The role focuses on AI-enabled ServiceNow features, solution validation, quality, compliance, and continuous improvement of software development and operations. The posting also labels the work “ServiceNow AI Developer (Entry Level),” while specifying a minimum of 5 years of experience.

Responsibilities

Develop features using ServiceNow Now Assist, Virtual Agent, and AI Search, supported by 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. Candidates need strong JavaScript, REST API, and ServiceNow platform development fundamentals; familiarity with App Engine, Flow Designer, IntegrationHub, and Scoped Applications; and an understanding of LLMs, prompt engineering, and evaluation metrics.
The posting seeks 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 integrations, MID Server, OAuth, and SAML; and basic understanding of RAG, vector search, and orchestration frameworks.
Collaboration, communication, problem-solving, attention to detail, adaptability, curiosity, and continuous learning are also listed. The education requirement is 15 years of full-time education.

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

Skills for this role

ServiceNowNow AssistVirtual AgentAI SearchApp Engine StudioFlow DesignerIntegrationHubJavaScriptREST APIsScoped ApplicationsLarge Language ModelsPrompt EngineeringAI EvaluationRetrieval-Augmented GenerationVector SearchSOAPMID ServerOAuthSAMLAgileResponsible AISecure EngineeringCommunicationCollaborationProblem Solving

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Ship AI-enabled ServiceNow features
The posting calls for developing Now Assist, Virtual Agent, and AI Search features with App Engine Studio, Flow Designer, and IntegrationHub. Prepare to explain how you would take a feature from configuration or development through validation for production use.
Make AI behavior testable
The role includes authoring prompts and evaluators, contributing to RAG strategies and testing frameworks, and understanding evaluation metrics. Prepare to discuss how you would measure whether an AI feature works and identify failures.
Apply sound platform and integration engineering
JavaScript, REST APIs, and ServiceNow development are emphasized, alongside Scoped Applications and platform rules and scripts. The posting also mentions SOAP/REST integrations, MID Server, OAuth, and SAML. Prepare to explain design choices at the boundary between ServiceNow and other systems.
Maintain quality, security, and collaboration
The role calls for production-ready software, Responsible AI, secure engineering, and work with architects and product owners in agile pods, sprints, and code reviews. Prepare examples of how technical review and cross-functional decisions improve a release.

Likely challenges to think through

Balancing AI usefulness with predictable behavior
Preparation hypothesis, not a stated employer problem: Now Assist, Virtual Agent, AI Search, and agentic workflows may be useful without behaving consistently in every case. Prepare to discuss evaluation cases, failure handling, and when a workflow should avoid automated action.
Choosing between platform configuration and custom logic
Preparation hypothesis: App Engine Studio and Flow Designer can speed delivery, while JavaScript, Business Rules, and integrations may offer more control. Prepare to explain how you would weigh maintainability, testability, and platform fit when choosing an approach.
Moving quickly without weakening safeguards
Preparation hypothesis: sprint delivery and workflow automation can create tension with the posting’s quality, compliance, Responsible AI, and secure-engineering expectations. Prepare to describe checks you would build into development and code review rather than defer until release.

Practice your answers

Technical practice

How would you structure a ServiceNow feature using JavaScript, Business Rules, client scripts, and UI policies?

What to coverSuggested preparation: Explain which logic belongs on the server versus the client, how it interacts with the data model, and how you would avoid conflicting behavior. Discuss how a Scoped Application affects design and testing.

How would you configure and validate a Now Assist feature?

What to coverSuggested preparation: Walk through the intended user task, configuration choices, and checks for useful, accurate output. Explain how you would handle responses that are incorrect or inappropriate before release.

How would you design a Virtual Agent interaction for a ServiceNow workflow?

What to coverSuggested preparation: Describe how you would guide the user, collect needed information, and connect the interaction to the workflow. Address testing for unclear requests and unsuccessful outcomes.

How would you assess and tune AI Search results?

What to coverSuggested preparation: Define what a relevant result means for a user task and how you would compare results before and after a change. Discuss trade-offs between broad coverage and precise results.

When would you use App Engine Studio, Flow Designer, or IntegrationHub in a feature?

What to coverSuggested preparation: Compare their roles in building an application, automating a workflow, and connecting another system. Explain how you would choose an approach that remains maintainable and testable.

How would you troubleshoot a ServiceNow integration that is failing?

What to coverSuggested preparation: Trace the request, authentication, connectivity, and response before changing code. Be ready to distinguish where REST or SOAP, MID Server, OAuth, or SAML may be relevant without assuming every integration uses them.

How would you apply an agentic pattern to workflow automation or developer assistance?

What to coverSuggested preparation: Describe how tasks, tool use, and stopping conditions could be bounded. Explain when a simpler deterministic workflow would be preferable and how you would validate the agent's actions.

How would you write and evaluate a prompt for an AI-enabled feature?

What to coverSuggested preparation: Explain how the prompt specifies the task and constrains output, then identify evaluation criteria suited to that task. Discuss how representative test cases and failure analysis would guide revisions.

What would you consider when adding retrieval-augmented generation to a ServiceNow solution?

What to coverSuggested preparation: Explain retrieval, vector search, and how retrieved content could inform a response. Discuss source relevance, stale or missing information, and tests that distinguish retrieval failures from generation failures.

How would you decide whether an AI-enabled feature is ready for production?

What to coverSuggested preparation: Cover functional testing, AI evaluation, security, Responsible AI, and compliance considerations stated in the role. Explain how you would investigate failures and use findings to improve the feature after release.

Behavioural practice

Tell me about a time you aligned technical work with architects or product owners.

What to coverSuggested preparation: Give the situation, your actions to clarify requirements or trade-offs, and the result. Make your contribution to a shared decision clear.

Describe a code review in which you improved quality or changed your approach.

What to coverSuggested preparation: State the context, the feedback you gave or received, the action taken, and the result. Explain how you handled disagreement constructively.

Tell me about a difficult defect you investigated.

What to coverSuggested preparation: Describe the symptoms, how you narrowed down the cause, the fix or mitigation, and the result. Highlight the evidence you used rather than assuming the first explanation was correct.

Describe a time priorities changed during a sprint or client-focused delivery.

What to coverSuggested preparation: Set out the situation, how you communicated and adjusted your work, and the outcome. Include any trade-off you raised to protect quality.

Tell me about a time you learned an unfamiliar capability to solve a work problem.

What to coverSuggested preparation: Explain the need, how you learned and tested the capability, and the result. Distinguish what you verified from what remained uncertain.

Sharpen your knowledge

Topics to prepare

ServiceNow platform design
The posting requires ServiceNow development fundamentals and mentions Scoped Applications, data models, UI policies, Business Rules, and client scripts. As preparation, sketch a scoped application and explain where its data, server-side rules, and client-side behavior belong.
ServiceNow AI features
The role names Now Assist, Virtual Agent, and AI Search, including configuration and search tuning. As preparation, compare what each would do in a sample service workflow and identify what you would validate before release.
LLMs, RAG, and evaluation
The posting asks for understanding of LLMs, prompts, evaluation metrics, RAG, vector search, and orchestration concepts. As preparation, diagram a retrieval-based answer flow and define checks for answer accuracy and unsupported claims.
Agentic automation and safeguards
The role calls for agentic patterns, Responsible AI, secure engineering, quality, and compliance. As preparation, outline an automated workflow, its permitted actions, failure cases, and points where a person should review the result.
Integration and authentication concepts
The posting specifies REST APIs and awareness of SOAP/REST integrations, MID Server, OAuth, and SAML. As preparation, explain which concerns each addresses in a hypothetical ServiceNow integration and where authentication or data exposure could fail.

Skills to revise

Write and review ServiceNow JavaScript
Strong JavaScript and ServiceNow development fundamentals are specified. As practice, draft a Business Rule and a client script for a simple record update, then review them for unintended updates and validation gaps.
Build a scoped workflow
The role uses App Engine Studio and Flow Designer and seeks familiarity with Scoped Applications. If a practice environment is available, build a small scoped workflow, test its success and failure paths, and explain the design choices.
Prototype an integration
IntegrationHub and REST APIs are named in the posting. As practice, map a Flow Designer integration step to a sample REST request and response; document error handling and how authentication would be managed, without assuming a specific external system.
Configure and test AI interactions
The role develops features using Now Assist, Virtual Agent, and AI Search. If access is available, configure a small example interaction and test whether responses or search results are relevant, safe, and useful; otherwise, write the configuration and test plan.
Create prompts and evaluators
The posting explicitly calls for authoring prompts and evaluators and contributing to testing frameworks. As practice, write a prompt for a service-workflow task, assemble a few representative and failure-case inputs, and score outputs against stated criteria.
Practice a code-review discussion
The role involves agile pods, sprints, and code reviews with architects and product owners. As preparation, review a sample change and explain its behavior, tests, security considerations, and open questions in a concise review note.

Your preparation checklist

Prepare a ServiceNow project walkthrough
If you have a relevant example, outline the problem, your contribution, architecture, validation and outcome. Focus on a Now Assist, Virtual Agent or AI Search feature; otherwise, use a clearly labeled practice scenario.
Rehearse platform implementation decisions
Prepare a small example showing how JavaScript, a scoped application, Business Rules or client scripts, and Flow Designer could work together. Explain data-model choices and what you would test.
Sketch an AI-enabled workflow
For practice, diagram how App Engine Studio, Flow Designer and IntegrationHub could support an agentic automation. Identify where a human reviews or overrides its actions.
Prepare prompts and evaluation examples
Draft a prompt, sample test cases and a simple evaluation rubric for a ServiceNow AI feature. Explain how you would check quality, failures and Responsible AI concerns; the posting specifically mentions prompts, evaluators and testing frameworks.
Review integration and retrieval trade-offs
Practice explaining a REST integration, including authentication and error handling. Also sketch when RAG or vector search might help, while distinguishing that practice design from any project you have actually delivered.
Gather delivery and collaboration evidence
If available, select examples of code reviews, sprint work with architects or product owners, secure engineering, and quality or compliance checks. State your own decisions and contributions precisely.
Write questions for the employer
Ask which ServiceNow AI features are in scope, how solutions are validated, and what ownership the role carries. Clarify the posting’s differing labels: “Team Lead/Consultant,” “ServiceNow AI Developer (Entry Level),” and a minimum of five years of experience.

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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