New opportunity

AI Developer

Xerox · Kolkata, India

About this role

Xerox is seeking an AI Developer in Kolkata, West Bengal, India, to help define and deliver AI initiatives across the organization. The role includes exploring agentic AI capabilities and building intelligent applications for IT and other business functions, with an emphasis on practical, globally scalable solutions that create measurable business value.

Responsibilities

Work across application architecture, development, integrations and AI-enabled solutions on multiple concurrent initiatives.
Develop full-stack applications, APIs and microservices; design and deploy cloud-native applications.
Build AI and agentic AI solutions, integrate them with enterprise systems and data sources, and support data engineering and transformation.
Apply DevOps, CI/CD, automation and secure software development practices. Work directly with product, architecture and business stakeholders.

Qualifications and capabilities:

The posting seeks experienced professionals with technical versatility, ownership, a problem-solving mindset and a focus on delivery; it does not specify a minimum number of years of experience.
Strong debugging skills, experience with Agile and SAFe delivery, and curiosity about emerging AI technologies are sought. The position is full-time and classified as an individual-contributor role.

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

Skills for this role

Full-stack developmentAPI developmentMicroservicesCloud-native application designCloud deploymentAI solution developmentAgentic AIEnterprise systems integrationData engineeringData transformationDevOpsCI/CDAutomationSecure software developmentDebuggingProblem-solvingAgileSAFe

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

Deliver AI with measurable business value
The role helps shape and deliver AI initiatives for IT and other business functions, including agentic AI and intelligent applications. Prepare to explain how you would connect an AI use case to a business outcome and evaluate whether it delivers value.
Build applications across the stack
The posting calls for full-stack development, APIs, microservices, and cloud-native design and deployment. Prepare to discuss architecture and implementation decisions across these layers.
Connect AI to enterprise data and systems
Enterprise integration, data engineering, and transformation are listed capabilities. Prepare to explain how data quality and integration choices affect an AI application.
Own reliable delivery across initiatives
The role emphasizes ownership across concurrent initiatives, secure development, debugging, DevOps, CI/CD, automation, and collaboration with product, architecture, and business stakeholders.

Likely challenges to think through

Balancing experimentation with practical delivery
A likely challenge, not a confirmed Xerox problem, is deciding when an emerging agentic AI approach is worth pursuing versus a simpler solution. Prepare to describe how you would test feasibility, value, and scalability before committing to an approach.
Integrating AI without sacrificing security
Because the role combines enterprise data integration with secure software development, a likely trade-off is enabling useful data access while controlling risk. Prepare to discuss how you would make and validate those design decisions.
Keeping concurrent work aligned
The posting mentions multiple initiatives and direct work with product, architecture, and business stakeholders. A likely difficulty is reconciling different priorities while maintaining delivery focus; prepare an approach to clarifying outcomes, dependencies, and trade-offs.

Practice your answers

Technical practice

How would you design a full-stack AI application for an internal business function?

What to coverThe posting calls for full-stack development and practical AI applications for IT and other functions. Suggested preparation: explain how you would divide responsibilities across the interface, application services and AI component, and how you would judge whether the design meets a business need.

When would you use a microservice rather than add an API to an existing application?

What to coverThe posting names API and microservices development. Suggested preparation: discuss service boundaries, integration needs and the trade-off between independent deployment and operational complexity.

How would you design and deploy an AI application for global scale?

What to coverThe posting emphasizes cloud-native deployment and globally scalable solutions. Suggested preparation: address capacity, reliability and deployment considerations without assuming a particular cloud platform.

How would you decide whether an agentic AI approach fits a use case?

What to coverThe posting specifically mentions exploring agentic AI capabilities. Suggested preparation: compare an agentic workflow with a simpler application flow, including where autonomy helps and where controls or human review would be prudent.

How would you evaluate whether an AI initiative creates measurable business value?

What to coverThe posting calls for impactful initiatives with measurable business value. Suggested preparation: connect a defined business problem to outcome measures, and distinguish those outcomes from technical performance measures.

How would you integrate an AI solution with enterprise systems and data sources?

What to coverEnterprise integration is an explicit capability in the posting. Suggested preparation: explain how you would handle interfaces, access to data and failures between systems while avoiding assumptions about Xerox’s specific systems.

What data preparation would you do before using enterprise data in an AI application?

What to coverThe posting names data engineering and transformation. Suggested preparation: cover data quality, transformation and validation, including how errors in source data could affect the application.

How would you use CI/CD and automation when delivering an AI-enabled application?

What to coverThe posting lists DevOps, CI/CD and automation practices. Suggested preparation: describe useful build, test and deployment checks, and how you would detect a problem after a change.

What secure-development concerns would you address in an enterprise AI application?

What to coverSecure software development is explicitly listed. Suggested preparation: discuss appropriate access controls, protection of sensitive data and validation at application and integration boundaries.

How would you debug a failure that crosses the application, an API and an AI component?

What to coverThe posting calls for strong debugging skills across development, integrations and AI-enabled solutions. Suggested preparation: describe a method for isolating the failing layer, gathering evidence and verifying the fix.

Behavioural practice

Tell me about a time you owned delivery across competing initiatives.

What to coverThe posting emphasizes ownership and execution across multiple concurrent initiatives. Suggested preparation: use a real situation, your prioritization and communication actions, and the result; explain any trade-offs you made.

Describe a time you worked with product, architecture and business stakeholders on a technical decision.

What to coverWorking directly with those stakeholder groups is stated in the posting. Suggested preparation: give the situation, how you reconciled differing needs, and the resulting decision or delivery outcome.

Tell me about a time you explored an emerging technology but had to decide whether to use it.

What to coverThe posting values curiosity and experimentation alongside practical delivery. Suggested preparation: describe the situation, how you tested usefulness and risks, and what decision followed; an example need not involve agentic AI.

Describe a time an Agile or SAFe delivery plan had to change.

What to coverAgile and SAFe delivery experience is listed in the posting. Suggested preparation: use a real situation, your actions with the team when priorities or constraints shifted, and the effect on delivery.

Tell me about a difficult technical problem you diagnosed and resolved.

What to coverThe posting calls for debugging and problem-solving skills. Suggested preparation: explain the symptoms and context, the evidence you used to narrow the cause, your actions and the result.

Sharpen your knowledge

Topics to prepare

AI and agentic AI design
Review when an intelligent application needs an agentic workflow rather than a simpler AI feature. As a preparation exercise, sketch both approaches for a hypothetical IT task and define a measurable outcome. The posting explicitly mentions agentic AI, intelligent applications, and business value; the task is illustrative, not a stated Xerox project.
Full-stack and cloud-native architecture
Diagram a small application’s user interface, API, microservices, and deployment boundaries; explain how the design could scale. This revises the posting’s full-stack, API, microservices, and cloud-native capabilities.
Enterprise integration and data flow
Trace a hypothetical data source through ingestion, transformation, and an application interface; identify where data errors or interface changes could arise. The posting calls out enterprise-system integration and data engineering.
Secure and automated delivery
Review how security checks, automated tests, and deployment stages fit into a development lifecycle. Draw a sample CI/CD flow and explain where a failed change would be caught. Secure development, DevOps, CI/CD, and automation are stated capabilities.
Delivery across stakeholders and initiatives
Practice explaining a technical trade-off in terms of business value, delivery scope, and dependencies across concurrent work. The posting mentions product, architecture, and business stakeholders, plus Agile and SAFe delivery experience.

Skills to revise

Prototype an AI workflow
As a preparation exercise, implement a small intelligent workflow using sample data, then test expected results and failure cases. This is relevant to AI and agentic AI solution development; no particular framework is specified in the posting.
Build an application and API
Create a small full-stack application backed by an API or microservice, and test its request handling. This directly practices the advertised full-stack, API, and microservices work.
Transform and integrate sample data
Connect a sample data source to an application, transform its records, and check how malformed input is handled. This practices the stated integration and data-transformation capabilities without assuming a particular Xerox system.
Deploy and troubleshoot a service
Deploy a small service in a cloud-native configuration, introduce a controlled fault, and use its output to diagnose and fix the issue. This combines the posting’s deployment and strong debugging expectations; no cloud provider is specified.
Automate a secure delivery check
Set up an example CI/CD sequence that runs tests and a security check before deployment, then demonstrate how it blocks a failing change. This practices the stated DevOps, automation, and secure-development capabilities.

Your preparation checklist

Prepare a full-stack project walkthrough
The posting calls for full-stack development, APIs, microservices and cloud-native deployment. Prepare a diagram and brief account of a project you worked on, covering your decisions, contribution, deployment and trade-offs. If no single project covers all four areas, use separate examples.
Sketch an AI application design
The role includes intelligent applications and exploration of agentic AI. As a preparation exercise, sketch a practical use case for an IT or business function, showing where an agent would help, where human oversight belongs, and how you would measure business value. Treat the design as a proposal, not a Xerox project.
Map an enterprise integration
The posting names enterprise systems, data sources, data engineering and transformation. Prepare a simple data-flow diagram that shows integration points, transformations, error handling and security considerations; mark any assumptions.
Gather delivery and debugging evidence
Prepare concise examples of a difficult problem you debugged and a change you delivered using DevOps, CI/CD or automation practices. Be ready to explain the checks you used and what you personally did.
Outline how you coordinate concurrent work
The role calls for ownership across multiple initiatives and direct work with product, architecture and business stakeholders, plus Agile and SAFe experience. Prepare an example of how you clarified priorities, resolved a trade-off and communicated progress; distinguish firsthand experience from approaches you would use.
Draft questions for the interviewers
Ask which AI use cases are priorities, what enterprise integration constraints matter most, how teams evaluate measurable value and global scale, and how this individual-contributor role works with stakeholders across concurrent initiatives.

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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