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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 using AI throughout the engineering lifecycle. The role focuses on AI-enabled ServiceNow features, solution validation, quality, compliance, and continuous improvement. It is listed as a full-time Senior Analyst position with an experience band of 2–5 years; the job description separately specifies a minimum of 3 years of experience.

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 RAG strategies and testing frameworks.
  • Work with architects and product owners in agile sprints and code reviews. Apply Responsible AI principles and secure engineering practices.

Qualifications and skills:

  • Required: ServiceNow; strong JavaScript, REST API, and ServiceNow platform development fundamentals. The posting requires 15 years of full-time education.
  • 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.
  • Exposure to ServiceNow data models, UI policies, Business Rules, and client scripts; awareness of SOAP/REST integrations, MID Server, OAuth, and SAML; and a basic understanding of RAG, vector search, and orchestration frameworks.
  • Collaboration, communication, problem-solving, attention to detail, adaptability, curiosity, and a continuous-learning mindset 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 ApplicationsLLMsPrompt EngineeringAI EvaluationRAGVector SearchWorkflow AutomationResponsible AIServiceNow Data ModelsUI PoliciesBusiness RulesClient ScriptsSOAPMID ServerOAuthSAMLAgile DevelopmentCommunicationProblem 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 developing Now Assist, Virtual Agent, and AI Search features using App Engine Studio, Flow Designer, and IntegrationHub. ServiceNow is the posting’s must-have skill.

  • Build on sound platform fundamentals

    JavaScript, REST APIs, and ServiceNow development underpin the work. The posting also names Scoped Applications, data models, UI policies, Business Rules, client scripts, and integration and authentication patterns.

  • Validate AI behavior and improve workflows

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

  • Deliver securely with the team

    The role calls for Responsible AI and secure engineering practices, plus collaboration with architects and product owners in agile sprints and code reviews. The role description emphasizes production-ready quality and compliance.

Likely challenges to think through

  • Balancing automation with control

    Preparation hypothesis: Agentic workflow automation may need clear limits to remain secure and reliable. Prepare to explain how you would bound actions, handle failures, and review outcomes against the posting’s Responsible AI and secure-engineering expectations.

  • Showing that AI features work consistently

    Preparation hypothesis: Prompt or search quality can be harder to assess than a conventional feature. Prepare an example approach to defining evaluation criteria, testing varied inputs, and using results to refine prompts, AI Search, or a RAG strategy.

  • Coordinating platform and integration changes

    Preparation hypothesis: A ServiceNow AI feature spanning flows, platform data, and external APIs may involve trade-offs between speed of delivery and maintainability. Prepare to discuss how you would clarify requirements with architects and product owners, then validate changes through tests and code review.

03

Practice your answers

Technical practice

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

What to coverThe posting names these platform components alongside JavaScript and ServiceNow data models. Suggested preparation: explain where each runs, how it affects data or the user interface, and how you would test for unintended effects.

How would you structure an AI-enabled ServiceNow feature using App Engine Studio and a Scoped Application?

What to coverThe role calls for AI-enabled features and familiarity with both App Engine and Scoped Applications. Suggested preparation: describe application boundaries, access to platform data, and the checks you would make before release.

How would you configure and validate a Now Assist feature?

What to coverNow Assist configuration is explicitly named in the posting. Suggested preparation: discuss the intended user task, how you would check output usefulness, and what you would do when an answer is inaccurate or inappropriate.

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

What to coverVirtual Agent is listed as a feature area for this role. Suggested preparation: explain how you would define the task, handle unclear user input, and verify that the interaction reaches the intended outcome.

How would you investigate poor results from AI Search?

What to coverThe posting specifically calls out AI Search tuning. Suggested preparation: describe how you would examine representative queries and results, distinguish relevance problems from missing content, and evaluate whether a change helps.

How would you connect a Flow Designer workflow to an external service?

What to coverFlow Designer, IntegrationHub, REST and SOAP integrations, MID Server, OAuth, and SAML all appear in the posting. Suggested preparation: explain when those components are relevant and how you would handle authentication, failures, and safe testing without assuming every integration needs them all.

What would you consider before using an agentic pattern for workflow automation?

What to coverThe role includes agentic patterns for workflow automation and developer assistance. Suggested preparation: compare an agentic approach with a more constrained workflow, including task boundaries, human oversight, and ways to detect incorrect actions.

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

What to coverThe posting asks for prompts, evaluators, testing frameworks, and an understanding of LLM evaluation metrics. Suggested preparation: describe a test set, criteria tied to the task, and how you would compare prompt revisions rather than relying on a few convincing examples.

How would you assess whether RAG would help a ServiceNow AI use case?

What to coverThe role calls for contributions to RAG strategies and basic understanding of vector search and orchestration frameworks. Suggested preparation: explain retrieval and grounding at a conceptual level, then discuss how you would test whether retrieved material improves answers or introduces irrelevant content.

What checks would you apply before shipping an AI-enabled ServiceNow feature?

What to coverThe role emphasizes production readiness, solution validation, quality, compliance, Responsible AI, and secure engineering. Suggested preparation: organize your answer around functional tests, AI-output evaluation, data access and security checks, and how you would respond to a failed check.

Behavioural practice

Tell me about a time you aligned technical work with a product owner or architect.

What to coverThe posting describes collaboration with architects and product owners in agile sprints. Use a real situation, explain how you clarified a decision or trade-off, and state the result.

Describe a code review that improved the quality of a change.

What to coverParticipation in code reviews and maintaining software quality are stated parts of the role. Give a real situation, the feedback or action you took, and the resulting change; avoid claiming an impact you cannot substantiate.

Tell me about a difficult software issue you investigated methodically.

What to coverThe posting seeks problem-solving and attention to detail. Describe the situation, how you narrowed down the cause and checked your fix, and what happened afterward.

Describe a time you adapted to a changing client-focused priority.

What to coverAdaptability in a fast-paced, client-focused environment is explicitly listed. Use a real example that shows the changed context, how you communicated and adjusted your work, and the result.

Tell me about something you had to learn to improve your engineering work.

What to coverCuriosity and continuous learning are named soft skills. Explain the situation, the steps you took to learn and apply the material, and what changed as a result.

02

Sharpen your knowledge

Topics to prepare

  • ServiceNow platform fundamentals

    Map a hypothetical request from the ServiceNow data model through a Business Rule, client script, and UI policy; explain what each controls. Relevant because the posting calls for platform development fundamentals and exposure to these components.

  • ServiceNow AI feature roles

    Compare when Now Assist, Virtual Agent, and AI Search would serve a hypothetical user request, including what AI Search tuning or Now Assist configuration might affect. Relevant because the role develops features with all three.

  • LLMs, evaluation, and RAG

    Explain how a prompt, retrieved content, vector search, and an evaluator could work together; choose metrics for checking answer quality. Relevant because the posting names prompt engineering, evaluation metrics, RAG, and vector search.

  • Agentic workflow boundaries

    Draw a hypothetical workflow that uses an AI step, then identify which actions need validation before execution. Relevant because the role implements agentic patterns for workflow automation and developer assistance.

  • Integration and authentication concepts

    Trace a hypothetical ServiceNow-to-external-system exchange and explain the roles of REST versus SOAP, MID Server, OAuth, and SAML where applicable. Relevant because the posting asks for REST fundamentals and awareness of these integration mechanisms.

  • Responsible AI and secure engineering

    Review a hypothetical AI-generated response for sensitive-data exposure, incorrect output, and unsafe downstream actions; state how each would be detected or contained. Relevant because the role explicitly applies Responsible AI principles and secure engineering practices.

Skills to revise

  • JavaScript and ServiceNow logic

    Write a small hypothetical Business Rule and client script, then check their behavior against a UI policy and the underlying data model. This practices the JavaScript and platform development fundamentals named in the posting.

  • Scoped application workflow

    Sketch or build, if a practice instance is available, a scoped application flow in App Engine Studio and Flow Designer; identify where IntegrationHub would connect an external step. These are named development tools in the role.

  • AI feature configuration

    In a practice instance, or on paper, configure a sample Now Assist or Virtual Agent interaction and propose an AI Search tuning check. This directly reflects the listed feature-development work; access to a practice instance is a preparation option, not a stated requirement.

  • Prompt and evaluator authoring

    Draft a prompt for a hypothetical ServiceNow support task, five test inputs, and an evaluator that flags unsupported answers. This practices the posting’s responsibility to author prompts and evaluators and contribute to testing frameworks.

  • REST integration implementation

    Draft a JavaScript REST request and response handler for a hypothetical ServiceNow integration, including an authentication and error-handling plan. This exercises the stated JavaScript and REST fundamentals without assuming a specific employer API.

  • Code review communication

    Prepare a short review of a hypothetical AI-enabled workflow change: describe its behavior, tests, quality risks, and questions for an architect or product owner. This mirrors the posting’s agile sprint and code-review collaboration.

04

Your preparation checklist

  • Prepare a ServiceNow feature walkthrough

    The posting names Now Assist, Virtual Agent, AI Search, App Engine Studio, Flow Designer, and IntegrationHub. Prepare one project walkthrough showing which tools you used, your contribution, the workflow, and how you validated the result. If you lack a matching project, use a clearly labeled design example.

  • Assemble evidence of platform fundamentals

    The posting calls for JavaScript, REST APIs, and ServiceNow development. Bring a concise example of a Business Rule, client script, or scoped application, explaining the data model, API behavior, and a debugging decision.

  • Practice an AI-enabled workflow design

    As a preparation exercise, sketch a ServiceNow workflow that uses an agentic pattern for automation or developer assistance. Show its triggers, tool or integration calls, human checks, and failure handling; do not present the sketch as an Accenture project.

  • Draft a prompt and evaluation plan

    The role involves prompts, evaluators, RAG strategies, and testing frameworks. Prepare a sample prompt and a small test table covering expected behavior, evaluation metrics, retrieval relevance, and failure cases.

  • Explain security and Responsible AI trade-offs

    The posting explicitly calls for secure engineering and Responsible AI. Prepare a short review of data access, sensitive information, authentication, and how you would test or mitigate unsafe AI outputs.

  • Rehearse collaboration and code-review examples

    The role involves agile pods, architects, product owners, sprints, and code reviews. Prepare one example showing how you clarified a requirement, responded to review feedback, and improved quality; distinguish your own actions from the team's.

  • Write targeted questions for the employer

    Ask which ServiceNow AI features are in scope, how solution quality is evaluated, and how architects and product owners divide decisions. You can also clarify the posting's 2–5-year listing, separate three-year minimum, and 'Entry Level' wording.

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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