New opportunity

Python Gen AI

Infosys Limited · Bangalore, India

About this role

Infosys is hiring for a Python Gen AI role in Bangalore within its Application Development and Maintenance service line. The posting specifies 3–5 years of work experience and lists Python and basic generative AI as primary technical skills.

Responsibilities

Carry out design, development, validation and support activities for client technology projects, contributing to efficient programs and systems.
Gather detailed client requirements and specifications, translate functional and nonfunctional needs into system requirements, and design and code complex programs.
Estimate work requirements and provide project-estimation input to Technology Leads and Project Managers. Write test cases and scenarios based on specifications.

Qualifications and capabilities:

An educational qualification in Bachelor of Engineering, BTech, BSc, BCA, MTech, MSc or MCA.
Knowledge of design principles, architectural fundamentals, performance engineering, quality processes and estimation techniques; a basic understanding of the project domain.
Understanding of the software development life cycle and agile methodologies, awareness of current technologies and trends, and logical problem-solving and collaboration skills.

Preferred skills: Python and basic generative AI are also listed in the posting's preferred-skills section.

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

Skills for this role

PythonGenerative AISoftware designSoftware architecturePerformance engineeringRequirements analysisSoftware testingSDLCAgile methodologiesProject estimationProblem solvingCollaboration

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

Translate client needs into system requirements
The posting calls for gathering detailed client specifications and converting functional and nonfunctional needs into system requirements. Prepare to explain how you clarify ambiguities and make requirements actionable.
Design and develop efficient Python systems
The role requires designing and coding complex programs, with Python and basic generative AI listed as primary skills. Prepare a concrete explanation of design choices, code structure and efficiency; no specific AI framework is named.
Validate and support delivered work
Design, development, validation and support are all stated responsibilities, and test cases must follow specifications. Prepare to show how tests trace to requirements and how you investigate defects after delivery.
Contribute credible work estimates
The posting expects input to project estimates for Technology Leads and Project Managers. Prepare to break work into tasks and explain assumptions, dependencies and uncertainty rather than offering an unsupported single figure.

Likely challenges to think through

Reconciling incomplete requirements with delivery
A likely challenge is deciding when a client requirement is clear enough to implement without overlooking nonfunctional needs. Prepare a hypothetical example showing clarification, documented assumptions and the resulting system requirement; this is a preparation scenario, not a reported client issue.
Balancing efficiency with validation
Complex Python work and basic generative AI may require a trade-off between implementation speed, performance and dependable test coverage. Prepare to explain what you would measure and which specification-based cases you would test; the posting does not identify a particular AI use case.
Estimating before every dependency is known
Providing useful estimates while requirements and technical details evolve may be difficult. Prepare a task breakdown with ranges, explicit assumptions and points at which you would revise the estimate; no employer-specific estimation process is stated.

Practice your answers

Technical practice

How would you turn a client's functional and nonfunctional needs into system requirements?

What to coverSuggested preparation: Explain how you clarify ambiguous needs, define measurable acceptance criteria, and trace requirements back to the client's specifications. Distinguish what the system must do from constraints such as performance.

How would you structure a complex Python program so it remains maintainable?

What to coverSuggested preparation: Discuss clear interfaces, separation of responsibilities, and handling errors at appropriate boundaries. Explain how you would balance readability with the need to build an efficient system.

What basic generative AI limitations would you consider when adding generated output to an application?

What to coverSuggested preparation: Cover output variability, inaccurate responses, and the need to validate results against the intended use. Describe how you would decide whether a generated response is acceptable without assuming a particular model or tool.

How would design principles and architectural fundamentals guide a new application component?

What to coverSuggested preparation: Explain how responsibilities, dependencies, and interfaces follow from the requirements. Discuss a trade-off between a simpler design and one that better accommodates likely change.

How would you derive test cases and scenarios from a specification?

What to coverSuggested preparation: Include expected behaviour, boundary conditions, invalid inputs, and traceability to requirements. Explain how you would identify gaps or ambiguities before treating the test set as complete.

How would you investigate a Python program that is slower than its nonfunctional requirements allow?

What to coverSuggested preparation: Start by confirming the performance target and measuring where time is spent. Discuss how you would compare a proposed optimisation with its effects on correctness and maintainability.

How would you estimate the work needed to design, build, and validate a requested change?

What to coverSuggested preparation: Break the work into activities, state assumptions and dependencies, and account for testing and uncertainty. Explain what information you would pass to a Technology Lead or Project Manager and when you would revise the estimate.

How would you diagnose and resolve a defect reported during application support?

What to coverSuggested preparation: Describe how you would reproduce and isolate the problem, check its impact against expected behaviour, and validate a fix. Include how you would reduce the risk of the same defect recurring.

How do validation and quality checks fit into iterative software development?

What to coverSuggested preparation: Connect requirements, development, testing, and support across the software development life cycle. Explain how feedback in an agile iteration could change priorities while preserving agreed quality checks.

Behavioural practice

Tell me about a time you clarified an ambiguous stakeholder requirement.

What to coverSuggested preparation: Use a real situation, the questions you asked and actions you took to resolve ambiguity, and the resulting change to the specification or work. Distinguish what was agreed from what you initially inferred.

Describe a time you collaborated to resolve a difficult development problem.

What to coverSuggested preparation: Give the situation, your specific actions alongside others, and the result. Show how you used evidence and shared decisions rather than presenting the outcome as solely your work.

Tell me about a time your estimate or delivery plan needed to change.

What to coverSuggested preparation: Explain the original situation and assumptions, what new information arose, and how you communicated and acted on it. State the result, including any lesson that improved later estimates.

Describe a time you found a quality issue during validation or support.

What to coverSuggested preparation: Set out the situation, how you investigated and prioritised the issue, and the actions you took to verify the resolution. Explain the result for the application or its users without overstating your contribution.

Tell me about a time changing requirements affected your work in an agile team.

What to coverSuggested preparation: Describe the situation, how you coordinated the change and adjusted your development or testing work, and the result. Highlight how you kept the revised work aligned with the agreed requirements.

Sharpen your knowledge

Topics to prepare

Basic generative AI concepts
Posting: Generative AI - Basic is a primary and preferred skill. Revision exercise: explain how generated output differs from deterministic program output and why it needs validation. This is a suggested way to prepare, not a specified project or framework.
Design principles and architectural fundamentals
Posting: knowledge of design principles and architectural fundamentals is listed. Revision exercise: sketch a small Python system, identify its components and responsibilities, and explain one design trade-off.
Requirements and system specifications
Posting: the role gathers client requirements and translates functional and nonfunctional needs into system requirements. Revision exercise: turn a short client request into separate functional requirements, nonfunctional constraints, and questions to clarify.
Performance engineering and quality
Posting: understanding of performance engineering and knowledge of quality processes are listed. Revision exercise: given a slow or unreliable program, distinguish a performance concern from a correctness concern and propose a way to check each.
SDLC, agile and estimation
Posting: SDLC, agile methodologies and estimation techniques are listed; the role supplies estimation input to Technology Leads and Project Managers. Revision exercise: break a sample change into development, validation and support tasks, then explain your estimates and assumptions.

Skills to revise

Implementing Python programs
Posting: Python is a primary and preferred skill, and the role designs and codes complex programs. Practice implementing a small program from a written specification, then refactor it into clear functions and handle invalid input.
Writing specification-based tests
Posting: the role writes test cases and scenarios based on specifications. Practice drafting normal, boundary and failure cases for the Python program, then run them and record expected versus actual results.
Translating client needs into a design
Posting: the role gathers detailed requirements and converts them into system requirements. Practice taking an ambiguous request, writing clarifying questions, and producing a brief design that traces each component to a requirement.
Diagnosing and supporting a change
Posting: design, development, validation and support are part of the role. As a preparation suggestion, introduce a defect into the practice program, reproduce it, fix it and rerun relevant tests; no particular support tooling is specified.

Your preparation checklist

Map the posting to preparation evidence
Make a one-page list of the role’s stated areas: Python, basic generative AI, requirements, design, validation, support and estimation. Note an example you could discuss for each; leave gaps as topics to practice, not claims of experience.
Prepare a Python project walkthrough
Choose work you can accurately describe, or use a clearly labeled practice example. Sketch the requirements, code structure, design decisions, tests, performance considerations and support or maintenance work. Explain your own contribution where applicable.
Practice a basic generative AI explanation
Prepare a short walkthrough of a simple Python-based generative AI use case, including inputs, outputs, limitations and how you would check results. This is preparation for the posting’s stated basic generative AI skill, not a claim that a particular AI architecture is required.
Work through a requirements-to-design exercise
Using a hypothetical client request, write clarifying questions, functional and nonfunctional requirements, a small system design and the main Python components. Explain the design principles and trade-offs you chose.
Draft tests and a work estimate
For that exercise, write representative test cases and validation scenarios tied to the specifications. Break implementation into tasks, estimate the effort with assumptions and identify what you would raise with a Technology Lead or Project Manager.
Prepare delivery examples and employer questions
Outline an accurate example of collaboration across development, validation or support and how work was managed through an SDLC or agile process. Ask how this role divides those activities, what client domain it serves and what level of generative AI work is expected.

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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