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AI Native Software Engineer

Accenture · Bengaluru, India

About this role

Accenture is seeking an AI Native Software Engineer in Bengaluru to build and ship production-ready software with AI integrated into the engineering lifecycle. The position is listed as a full-time Senior Analyst role with a 2–5-year experience band; the job description separately specifies a minimum of 3 years of experience. ServiceNow is the required skill.

Responsibilities

  • Develop AI-enabled ServiceNow features using 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.
  • Develop and validate solutions, maintain quality and compliance, and improve software engineering and operations practices. 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:

  • Requires 15 years of full-time education and strong fundamentals in JavaScript, REST APIs and ServiceNow platform development.
  • Seeks familiarity with ServiceNow App Engine, Flow Designer, IntegrationHub and Scoped Applications; understanding of LLMs, prompt engineering and evaluation metrics; and knowledge of Virtual Agent, AI Search tuning and Now Assist configuration.
  • Also calls for exposure to ServiceNow data models, UI policies, Business Rules and client scripts; awareness of SOAP/REST integration patterns, MID Server, OAuth and SAML; and basic understanding of RAG, vector search and orchestration frameworks.
  • Values curiosity, continuous learning, communication, collaboration, problem-solving, attention to detail and adaptability in client-focused environments.

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 SearchWorkflow AutomationResponsible AISOAPMID ServerOAuthSAMLAgile DevelopmentCommunicationCollaborationProblem 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 AI-enabled ServiceNow features

    The role calls for production-ready features using Now Assist, Virtual Agent and AI Search, built with App Engine Studio, Flow Designer and IntegrationHub.

  • Build and evaluate AI workflows

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

  • Apply ServiceNow and integration fundamentals

    ServiceNow is the required skill. The description emphasizes JavaScript, REST APIs and platform development, with familiarity in scoped applications, platform data and integration patterns.

  • Deliver securely with the team

    The role includes validating solutions, maintaining quality and compliance, applying Responsible AI and secure engineering practices, and working with architects and product owners in sprints and code reviews.

Likely challenges to think through

  • Balancing AI usefulness with reliability

    A likely challenge is making AI Search, assistants and agentic workflows useful without accepting inconsistent outputs. Prepare to explain how prompts, evaluators and testing would reveal failures before release; this is a preparation hypothesis, not a stated employer problem.

  • Automating across platform boundaries

    Connecting ServiceNow workflows to other systems may require balancing automation against authentication, data access and secure engineering. Prepare a concrete approach to validating REST or SOAP integrations and handling access safely; the posting does not identify a specific integration project.

  • Moving quickly without weakening controls

    AI-native delivery in agile pods may create tension between iteration speed and quality, compliance and code review. Prepare to describe how you would make those checks part of a sprint rather than leave them until release; this is an inference from the listed duties.

03

Practice your answers

Technical practice

How would you structure a ServiceNow feature using a Scoped Application, its data model, and JavaScript?

What to coverThe posting calls for ServiceNow platform development, Scoped Applications, data models, and JavaScript fundamentals. Suggested preparation: explain how you would separate client scripts, UI policies, and Business Rules, and how you would validate their behavior.

How would you build and troubleshoot a workflow using App Engine Studio, Flow Designer, and IntegrationHub?

What to coverThese tools are named for developing AI-enabled ServiceNow features. Suggested preparation: describe where each fits, how data moves through the workflow, and how you would isolate a failed step.

How would you evaluate a ServiceNow integration that uses REST or SOAP?

What to coverThe posting names REST APIs, SOAP/REST patterns, MID Server, OAuth, and SAML. Suggested preparation: compare relevant integration and authentication choices, then explain how you would diagnose a connectivity or authorization failure without assuming every component is needed.

How would you configure and validate a Now Assist feature?

What to coverThe role explicitly includes Now Assist configuration and AI-enabled feature development. Suggested preparation: describe the intended user task, how you would check output usefulness and accuracy, and when the feature should defer to a human.

How would you design and test a Virtual Agent interaction?

What to coverVirtual Agent is named among the features this role develops. Suggested preparation: cover conversation paths, handling an unclear request, and tests that show whether the interaction completes its intended task.

How would you tune AI Search when users cannot find relevant results?

What to coverThe posting calls for knowledge of AI Search tuning. Suggested preparation: explain how you would inspect example queries and results, assess relevance, and compare performance before and after a change.

How would you bound an agentic workflow for automation or developer assistance?

What to coverImplementing agentic patterns for those uses is a stated responsibility. Suggested preparation: describe what the agent may do autonomously, where checks or human review belong, and how you would detect an incorrect action.

How would you write and evaluate prompts for an AI-enabled ServiceNow feature?

What to coverThe posting calls for authoring prompts and evaluators and understanding evaluation metrics and testing frameworks. Suggested preparation: describe representative test cases, criteria for acceptable responses, and how you would investigate a regression after a prompt change.

When would a RAG approach help, and how would you assess its retrieval results?

What to coverThe posting asks for contributions to RAG strategies and basic understanding of vector search and orchestration frameworks. Suggested preparation: explain the retrieval-to-generation flow, how you would check whether retrieved material supports an answer, and the trade-off between coverage and irrelevant context.

How would you balance delivery, quality, Responsible AI, and secure engineering?

What to coverThe role calls for production-ready software, validation, compliance, Responsible AI, and secure engineering. Suggested preparation: describe checks for unsafe or unreliable AI behavior and how you would decide whether a feature is ready to ship.

Behavioural practice

Tell me about a time you worked with product and technical stakeholders to resolve a delivery trade-off.

What to coverThe posting describes agile pods with architects and product owners. Suggested preparation: use a real situation, your actions to clarify the trade-off and communicate a decision, and the result.

Describe a time a code review changed your approach.

What to coverParticipation in code reviews is a stated responsibility. Suggested preparation: give the situation, how you responded to feedback or raised a concern, and the effect on the work.

Tell me about a defect you traced to a small but consequential detail.

What to coverThe posting values problem-solving and attention to detail while maintaining quality. Suggested preparation: explain the situation, the steps you took to isolate and verify the cause, and the result without overstating your contribution.

Describe a time you had to learn quickly as client needs changed.

What to coverThe posting values curiosity, continuous learning, and adaptability in client-focused environments. Suggested preparation: give the situation, what you learned and changed in your approach, and the result for the work or stakeholders.

02

Sharpen your knowledge

Topics to prepare

  • ServiceNow application architecture

    Draw a scoped application’s data model and trace when a UI policy, client script and Business Rule act. This revises the ServiceNow platform development and data-model knowledge named in the posting.

  • Integration and authentication patterns

    Compare when a ServiceNow integration would use REST or SOAP, what role MID Server could play, and how OAuth differs from SAML. The posting calls for awareness of these patterns and mechanisms.

  • LLM prompts and evaluation

    For a hypothetical ServiceNow assistant response, define a prompt, an evaluator and two measurable quality checks. This addresses the stated understanding of LLMs, prompt engineering and evaluation metrics.

  • RAG and search concepts

    Diagram retrieval, vector search and answer generation; then explain how search relevance affects the answer. The role calls for basic RAG and vector-search understanding and AI Search tuning knowledge.

  • Agentic workflows and Responsible AI

    Sketch an agentic workflow for a routine ServiceNow task and identify where human review, data protection and failure handling belong. The posting mentions agentic automation, Responsible AI and secure engineering; the workflow is a preparation example, not an advertised project.

Skills to revise

  • JavaScript-based ServiceNow development

    In a practice environment, implement a small Business Rule and client script, then test expected and invalid inputs. This exercises the stated JavaScript fundamentals and exposure to ServiceNow scripting.

  • Scoped app and workflow building

    Build a sample scoped application with App Engine Studio and a simple Flow Designer workflow, documenting its trigger and outcomes. Both development areas are named in the role.

  • IntegrationHub and REST implementation

    Create or outline a Flow Designer integration step that calls a sample REST endpoint; check authentication, error handling and response mapping. This practices the advertised IntegrationHub and REST API work without assuming a particular client system.

  • Now Assist, Virtual Agent and AI Search configuration

    In a practice instance, configure a small Virtual Agent interaction and inspect how Now Assist configuration and AI Search results could support it; record one search-tuning change to test. These are the AI-enabled ServiceNow features named in the posting.

  • Prompt and evaluator testing

    Write two prompt variants for the same hypothetical workflow request, assemble a small set of test inputs and score the outputs against explicit criteria. The role calls for authoring prompts and evaluators and contributing to testing frameworks.

  • Secure validation and code review

    Review a sample ServiceNow change for access controls, unsafe data exposure, test coverage and an actionable code-review comment. This is a suggested exercise tied to the posting’s quality, compliance, secure engineering and code-review responsibilities.

04

Your preparation checklist

  • Build a role-evidence sheet

    List examples you can discuss for ServiceNow development, JavaScript and REST APIs. Note the posting’s minimum of three years’ experience and 15 years of full-time education; leave any gaps in evidence unclaimed.

  • Prepare a ServiceNow project walkthrough

    Choose a project you worked on and outline the problem, your contribution, platform components, validation and outcome. If relevant, show how data models, Business Rules, client scripts or UI policies affected the design.

  • Sketch an AI-enabled feature

    As a preparation exercise, diagram a ServiceNow feature using one of the named capabilities—Now Assist, Virtual Agent or AI Search—and show where App Engine Studio, Flow Designer or IntegrationHub would fit. Label proposed choices rather than presenting the design as past work.

  • Work through an integration design

    Prepare a short example of a ServiceNow integration using JavaScript and REST. Be ready to explain when SOAP, MID Server, OAuth or SAML might matter; the posting asks for awareness of these patterns, not a specific integration project.

  • Draft an AI evaluation plan

    Write sample prompts and evaluation criteria for a proposed workflow-automation or developer-assistance use case. Include how you would test responses and, if retrieval is useful, what you would check in a RAG or vector-search approach.

  • Document quality and safety checks

    Create a concise test and review checklist for the proposed feature covering correctness, access controls, sensitive data, failure handling and Responsible AI concerns. Connect it to the role’s stated focus on production readiness, compliance and secure engineering.

  • Rehearse collaboration examples and questions

    Prepare a concise example of working through a sprint, code review or design decision with others. Bring questions about the team’s ServiceNow AI use cases, evaluation practices and how architects and product owners work with the agile pod.

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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