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AI Native Software Engineer

Accenture · Bengaluru, India

About this role

Accenture is hiring an AI Native Software Engineer in Bengaluru to build and ship production-ready software using AI throughout the engineering lifecycle. The role is listed as a full-time AI Native Software Engineering Senior Analyst position, with ServiceNow as the required skill.

Responsibilities

  • Develop AI-enabled ServiceNow features using Now Assist, Virtual Agent, AI Search, App Engine Studio, Flow Designer and IntegrationHub.
  • Implement agentic approaches to workflow automation and developer assistance. Write prompts and evaluators, and contribute to retrieval-augmented generation (RAG) strategies and testing frameworks.
  • Develop and validate solutions while maintaining quality and compliance. Work with architects and product owners in agile sprints and code reviews, apply Responsible AI principles and follow secure engineering practices.

Qualifications and skills:

  • The posting lists 2–5 years of experience in its role summary and separately requires a minimum of 3 years of experience. It 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 is specified.
  • Awareness of SOAP/REST integration patterns, MID Server and OAuth or SAML authentication, plus a basic understanding of RAG, vector search and orchestration frameworks.
  • Collaboration, communication, problem-solving, attention to detail, adaptability and continuous learning are also sought.

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 ServerOAuthSAMLServiceNow Data ModelsUI PoliciesBusiness RulesClient ScriptsAgentic AIWorkflow AutomationResponsible AISecure EngineeringAgile DevelopmentCommunicationCollaboration

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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 developing features with Now Assist, Virtual Agent and AI Search using App Engine Studio, Flow Designer and IntegrationHub. Prepare to explain how a feature moves from platform design through validation.

  • Build reliable workflow automation

    The posting specifies agentic patterns for workflow automation and developer assistance, backed by JavaScript, REST APIs and ServiceNow development fundamentals. Focus preparation on implementation choices and how to verify the resulting behavior.

  • Evaluate prompts and retrieval

    Authoring prompts and evaluators, contributing to RAG strategies and testing frameworks, and understanding evaluation metrics are stated duties. Prepare to discuss how you would test an AI feature rather than relying on a few successful outputs.

  • Maintain quality through collaboration

    The role calls for work with architects and product owners in agile pods, participation in sprints and code reviews, and application of Responsible AI and secure engineering practices. Prepare to describe how review and validation fit into delivery.

Likely challenges to think through

  • AI usefulness versus predictable behavior

    A likely challenge is making Now Assist, Virtual Agent or AI Search useful while keeping outputs testable. Prepare a concrete approach to prompts, evaluators and testing, and explain what you would do when results vary.

  • Automation versus platform constraints

    Agentic workflows may need to work within ServiceNow data models, Business Rules, client scripts and integrations. Prepare to reason through where Flow Designer or IntegrationHub fits, and when custom JavaScript or an API integration would be appropriate.

  • Delivery pace versus safeguards

    Sprint delivery could put pressure on validation, security and Responsible AI checks; this is a preparation hypothesis, not a stated Accenture problem. Prepare to explain how you would surface risks in code reviews and with architects or product owners before release.

03

Practice your answers

Technical practice

Suggested practice question: How would you decide whether ServiceNow logic belongs in a Business Rule, client script, or UI policy?

What to coverThe posting names JavaScript, ServiceNow data models, Business Rules, client scripts, and UI policies. As preparation, explain where each runs, how it affects user experience and data integrity, and how you would test the choice.

Suggested practice question: How would you structure an AI-enabled feature as a scoped ServiceNow application?

What to coverThe posting calls for AI-enabled features and familiarity with App Engine Studio and Scoped Applications. As preparation, discuss application boundaries, access to data, maintainability, and how you would validate the feature before release.

Suggested practice question: When would you use Flow Designer and IntegrationHub for workflow automation?

What to coverBoth tools are named in the responsibilities. As preparation, describe how you would map triggers and actions, handle failures, and decide which steps need an external integration.

Suggested practice question: How would you approach a feature using Now Assist and Virtual Agent?

What to coverThe role names Now Assist configuration and Virtual Agent knowledge. As preparation, distinguish assisted generation from a conversational workflow, and explain how you would check that responses and handoffs meet the feature's intended purpose.

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

What to coverThe posting explicitly mentions AI Search tuning. As preparation, discuss the relevance of returned results, gaps in searchable content, and a repeatable way to compare results before and after a change.

Suggested practice question: How would you plan a ServiceNow integration with another system?

What to coverThe posting names REST APIs, SOAP/REST patterns, IntegrationHub, MID Server, OAuth, and SAML. As preparation, explain how you would identify the integration and authentication needs, protect access, and troubleshoot unsuccessful requests without assuming every named component is required.

Suggested practice question: Where could an agentic pattern help automate a workflow, and where should it stop?

What to coverThe responsibilities include agentic patterns for workflow automation and developer assistance. As preparation, describe a bounded task, the actions it may take, and checks or human review you would consider before consequential actions.

Suggested practice question: How would you write and evaluate a prompt for an AI-enabled feature?

What to coverThe posting calls for prompts, evaluators, LLM understanding, and evaluation metrics. As preparation, explain how you would define the task and test cases, measure useful output and failures, and revise the prompt based on results.

Suggested practice question: 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, describe retrieval and generation at a high level, then discuss source relevance, unsupported answers, and how you would test whether retrieval helps.

Suggested practice question: How would you validate an AI-enabled ServiceNow change for production use?

What to coverThe role emphasizes production-ready software, testing frameworks, quality, compliance, Responsible AI, secure engineering, and code reviews. As preparation, explain the functional, security, and AI-output checks you would prioritize and the trade-offs you would raise in review.

Behavioural practice

Suggested practice question: Tell me about a time you aligned different stakeholders on a feature during a sprint.

What to coverThe posting describes working with architects and product owners in agile sprints. Use a real situation, your actions to clarify priorities or trade-offs, and the resulting decision or delivery outcome.

Suggested practice question: Tell me about a time code review changed your approach.

What to coverCode reviews and collaboration are stated parts of the role. Describe the feedback or disagreement, how you responded and verified the change, and what resulted.

Suggested practice question: Tell me about a difficult software issue you resolved through careful investigation.

What to coverThe posting seeks problem-solving and attention to detail. Give the situation, the evidence you gathered and actions you took, and the result; distinguish what you knew from what you initially suspected.

Suggested practice question: Tell me about a time you had to learn or adapt quickly to meet a changing need.

What to coverThe posting seeks curiosity, continuous learning, and adaptability in a client-focused environment. Explain the change, how you learned or adjusted your work, and the observable result without claiming experience you do not have.

02

Sharpen your knowledge

Topics to prepare

  • ServiceNow platform structure

    The posting calls for ServiceNow development, Scoped Applications, data models, UI policies, Business Rules and client scripts. Suggested exercise: sketch a scoped application and explain where its data, server-side rules and client-side behavior would belong.

  • LLMs, RAG and evaluation

    The posting specifies LLMs, prompt engineering, evaluation metrics and basic RAG and vector-search concepts. Suggested exercise: diagram a retrieval-to-answer flow and identify measures for answer quality and retrieval relevance.

  • Agentic workflow patterns

    Implementing agentic patterns for workflow automation and developer assistance is an explicit responsibility. Suggested exercise: outline an agent-assisted workflow, including its inputs, permitted actions and points requiring validation.

  • Integration and authentication concepts

    The posting asks for awareness of SOAP/REST patterns, MID Server, OAuth and SAML. Suggested exercise: compare when each integration or authentication concept is relevant to a ServiceNow-connected system.

  • Responsible delivery practices

    The role emphasizes quality, compliance, Responsible AI, secure engineering, agile sprints and code reviews. Suggested exercise: review a hypothetical AI-enabled feature for security, unsafe outputs and test coverage, then summarize what you would raise in a code review.

Skills to revise

  • Build ServiceNow application logic

    The posting requires strong JavaScript and ServiceNow fundamentals and exposure to Business Rules, client scripts and UI policies. Suggested exercise: implement a small scoped feature, then explain which logic runs on the server versus the client.

  • Configure AI-enabled experiences

    The responsibilities name Now Assist, Virtual Agent and AI Search; the qualifications also mention configuration and search tuning. Suggested exercise: in a practice environment, configure a small example using the features available to you and test its responses or search results.

  • Automate a workflow

    The posting names App Engine Studio, Flow Designer and IntegrationHub for developing AI-enabled ServiceNow features. Suggested exercise: build a short workflow in a practice environment, trace its inputs and outputs, and test a failure case.

  • Implement and troubleshoot an API exchange

    Strong REST API fundamentals are required, alongside awareness of SOAP/REST integrations and authentication. Suggested exercise: write JavaScript for a sample REST request and response, then check how it handles authentication and errors.

  • Write prompts and evaluators

    Authoring prompts and evaluators and contributing to testing frameworks are stated responsibilities. Suggested exercise: draft a prompt for a ServiceNow support scenario, create several test cases and score the outputs against explicit criteria.

04

Your preparation checklist

  • Organize requirement evidence

    The posting lists ServiceNow as required, a minimum of three years’ experience, and 15 years of full-time education; its summary also says 2–5 years. Prepare a concise record of relevant experience and education without assuming how Accenture reconciles the experience figures.

  • Prepare a ServiceNow project walkthrough

    Choose a real example, if available, that shows your JavaScript and platform-development work. Be ready to explain the data model, Business Rules or client scripts used, REST integration, your contribution, and how you validated the result.

  • Practice an AI-enabled workflow design

    As a preparation exercise, sketch a ServiceNow feature using a relevant combination of Now Assist, Virtual Agent or AI Search with Flow Designer and IntegrationHub. Identify the user need, integration points, and where a person should review an automated action.

  • Draft a prompt and evaluation example

    The role calls for prompts, evaluators, RAG strategies and testing frameworks. Prepare a sample prompt, a small test set and evaluation criteria; explain how you would check retrieved information and handle inaccurate or unsafe responses.

  • Prepare a quality and collaboration story

    Select a real example of working with reviewers or stakeholders in a sprint. Explain a code-review decision, testing approach, and how you addressed security, compliance or Responsible AI considerations where applicable.

  • Write targeted questions for the employer

    Ask which ServiceNow AI features the team is building, how architects and product owners divide design decisions, and what quality and Responsible AI checks are expected before a feature ships.

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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