New opportunity

Digital Product Manager (AI/ML, Fintech or Technology - Driven Organizations)

Franklin Templeton · Hyderabad, India

About this role

Franklin Templeton seeks a Digital Product Manager for its Digital Product Management–GOE team in Hyderabad, India. The team manages the Goals Optimization Engine, a business-to-business-to-consumer wealth management platform used across global markets. The role supports digital investment solutions, AI-enabled product opportunities and emerging technology initiatives in a regulated financial services environment.

Responsibilities

Analyze needs across advisory, retirement and private wealth; conduct user, stakeholder and market research; and guide product discovery, prioritization, requirements, launch and adoption.
Write product requirements, user stories and acceptance criteria. Partner with engineering, design, data and investment teams on scalable enhancements and digital investment experiences.
Evaluate digital assets, tokenization, blockchain-enabled workflows and related client experiences. Support go-to-market planning, internal enablement and adoption across channels and regions.
Coordinate client and partner deployments, readiness, training and post-launch feedback. Work with legal, compliance, risk and operations teams on regulated-market considerations; maintain documentation and release notes; support testing and user acceptance.
Define success metrics, build dashboards, track performance and adoption, and contribute to competitive analysis, business planning and roadmaps.

Qualifications

MBA and STEM undergraduate degree from a leading institution; 4–6 years of experience in product management, product strategy, business analysis or technology delivery.
Experience in fintech, wealthtech, asset management, digital banking, payments or technology-driven organizations; exposure to blockchain, tokenization, digital assets, wallets, smart contracts or Web3 concepts; and experience defining and launching product capabilities, MVPs or digital client experiences.
Strong analytical skills, Microsoft Excel proficiency, requirements-writing experience and advanced use of AI tools for product discovery, research, analysis, prototyping, documentation and communication. Ability to shape AI-enabled use cases, success metrics, workflows, risks and implementation tradeoffs. Familiarity with Agile methods, analytics tools, APIs, data flows and digital-asset concepts; strong prioritization, collaboration and stakeholder communication.
Preferred: CFA, CAIA, FRM, CQF or another relevant advanced credential.

The full-time position is 40 hours per week, with a 2:00 PM–11:00 PM IST shift. Listed benefits include professional development and educational assistance, insurance, an employee stock investment plan, 12 weeks of paternity leave, transport and onsite facilities.

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

Skills for this role

Product managementProduct strategyBusiness analysisUser researchMarket researchProduct requirementsUser storiesAcceptance criteriaProduct lifecycle managementGo-to-market planningStakeholder managementAI toolsAI product developmentData analysisMicrosoft ExcelAgile methodologiesBusiness intelligenceData visualizationDashboardsAPIsUser acceptance testingCompetitive analysisBlockchainTokenizationDigital assetsSmart contractsWeb3PrototypingRisk managementCommunication

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

Turn research into product priorities
The role analyzes advisory, retirement and private-wealth needs and conducts user, stakeholder and market research to guide discovery, prioritization and roadmaps.
Specify scalable digital wealth enhancements
The posting calls for clear requirements, user stories, acceptance criteria and development priorities, developed with engineering, design, data and investment teams for the Goals Optimization Engine.
Shape practical AI-enabled opportunities
The role calls for identifying AI-enabled use cases and defining their workflows, success metrics, risks and implementation trade-offs. It also emphasizes using AI tools to improve product discovery, analysis and documentation.
Evaluate emerging technology within regulated markets
The role evaluates digital assets, tokenization and blockchain-enabled workflows while working with legal, compliance, risk and operations on product considerations.
Carry releases through adoption and measurement
Duties include client and partner readiness, training, testing, user acceptance, release materials and post-launch feedback, alongside dashboards that track product performance and adoption.

Likely challenges to think through

Balancing shared-platform scale with varied needs
Preparation hypothesis: A global B2B2C platform serving several wealth segments may face tension between reusable capabilities and channel- or market-specific needs. Prepare a way to compare user evidence, implementation cost and adoption impact before prioritizing variants.
Separating promising technology from viable product value
Preparation hypothesis: AI and digital-asset ideas may be attractive before their client value, risks or delivery constraints are clear. Prepare to outline a narrowly scoped use case, measurable outcome, workflow, key dependencies and points for legal or risk review.
Coordinating a release beyond the build
Preparation hypothesis: A technically complete enhancement may still need partner readiness, training and acceptance across teams and regions. Prepare a release-readiness approach that connects acceptance criteria, documentation, feedback and adoption metrics.

Practice your answers

Technical practice

How would you discover product needs across advisory, retirement, and private wealth users?

What to coverSuggested answer focus: Explain how you would combine user and stakeholder research with market evidence, then distinguish needs by segment. Describe how you would validate a proposed digital investment experience with investment and client-facing teams before defining requirements.

How would you turn a business need into a development-ready product requirement?

What to coverSuggested answer focus: Walk through the problem statement, user story, acceptance criteria, and open decisions. Explain how you would check the requirement with engineering, design, data, and investment partners while keeping scope testable.

How would you prioritize enhancements to a digital wealth platform?

What to coverSuggested answer focus: Compare user value, evidence from research or competitive analysis, delivery effort, and regulated-market constraints. Explain how you would document trade-offs and revisit priorities as roadmap evidence changes.

How would you evaluate an AI-enabled product opportunity?

What to coverSuggested answer focus: Define the user workflow, the value AI would add, measurable outcomes, and risks before proposing an MVP. Discuss implementation trade-offs and how you would determine whether the use case merits further investment.

How would you use AI tools in product discovery without treating their output as established fact?

What to coverSuggested answer focus: Describe appropriate uses in research synthesis, requirements drafting, prototyping, or analysis. Explain how you would verify findings against source material and stakeholder input, especially for investment or regulatory claims.

How would you assess a tokenization or blockchain-enabled client experience?

What to coverSuggested answer focus: Explain the proposed client benefit and workflow, then identify relevant concepts such as wallets, custody, smart contracts, and data flows. Compare those potential benefits with operational and regulatory considerations rather than assuming the technology is warranted.

What would you examine when an API-dependent platform enhancement does not work as expected?

What to coverSuggested answer focus: Trace the intended user journey and data flow, clarify expected versus observed behavior, and work with engineering and data partners to isolate the failure. Discuss how interface dependencies and scalability affect the product decision and release scope.

How would you incorporate legal, compliance, risk, and operations input into a product proposal?

What to coverSuggested answer focus: Identify which aspects of the proposed workflow need review and bring the relevant teams in while options are still open. Explain how you would record decisions, unresolved risks, and resulting changes to requirements without presuming a particular rule applies.

How would you measure whether a launched capability is being adopted?

What to coverSuggested answer focus: Define success metrics tied to the intended user outcome, then describe an Excel analysis or dashboard that tracks usage and performance. Explain how you would investigate weak adoption, including whether the cause lies in the experience, deployment, or enablement.

How would you prepare a client or partner deployment for release?

What to coverSuggested answer focus: Cover user acceptance testing, readiness criteria, implementation materials, release notes, and training. Explain how you would coordinate launch and enablement across channels or regions, then use post-launch feedback to decide what to improve.

Behavioural practice

Tell me about a time stakeholders disagreed on a product requirement.

What to coverSuggested answer focus: Give the situation and each stakeholder's concern, then describe how you clarified the decision and worked toward agreement. State the result and what evidence showed whether the decision worked.

Describe a time you had to make progress with an ambiguous product opportunity.

What to coverSuggested answer focus: Explain what was unknown, the research or analysis you chose, and how you narrowed the options. Share the resulting decision and what you learned when it was tested.

Tell me about a time you managed competing product priorities.

What to coverSuggested answer focus: Set out the conflicting demands and the criteria you used to sequence work. Describe how you communicated the trade-off and what happened after the decision.

Describe a time risk or compliance input changed your delivery approach.

What to coverSuggested answer focus: Use a real situation, if applicable, to explain the concern, whom you involved, and how you adjusted the proposal or release plan. State the outcome without presenting any particular regulatory conclusion as universal.

Tell me about a launch or deployment where feedback called for a change.

What to coverSuggested answer focus: Explain the rollout context, how you gathered feedback from users or partners, and the action you took. Describe the result using an observed outcome rather than an assumed improvement.

Sharpen your knowledge

Topics to prepare

Digital wealth product context
The GOE team manages a business-to-business-to-consumer wealth platform, and the role covers advisory, retirement, and private wealth needs. As a revision exercise, explain how an end client's goal, an adviser’s workflow, and a partner’s delivery needs could lead to different product priorities; this is a hypothetical example, not a description of GOE features.
Product lifecycle and prioritization
The posting spans discovery, requirements, launch, adoption, and roadmap discussions. Compare two hypothetical enhancement requests and explain how research findings, expected value, delivery effort, and competing priorities would affect your decision.
AI-enabled product judgment
The role calls for shaping AI-enabled opportunities, including workflows, success metrics, risks, and implementation tradeoffs. Outline a hypothetical use case for a digital investment experience, then explain what evidence would justify testing it and what risks would need review.
Digital assets in regulated markets
The posting names tokenization, wallets, smart contracts, custody, blockchain-enabled workflows, and regulatory considerations. Trace a hypothetical tokenized-asset client journey and identify questions for legal, compliance, risk, and operations rather than assuming a specific regulatory answer.
Platform and delivery tradeoffs
A working understanding of APIs, data flows, platform products, and technology delivery tradeoffs is requested. Sketch a conceptual flow from a partner channel to a wealth platform and back; explain where data quality, scalability, and release dependencies could affect a product decision.

Skills to revise

Research synthesis
Practice turning sample user, stakeholder, and market observations into a one-page opportunity statement with evidence, open questions, and a proposed priority. This mirrors the role’s discovery and research responsibilities.
Requirements writing
For a hypothetical digital wealth enhancement, draft a short product requirement, two user stories, and testable acceptance criteria. The posting explicitly calls for these artifacts and for translating business needs into development priorities.
AI-assisted product work
Use an AI tool to draft a research summary or requirement from fictional inputs, then check claims against those inputs, correct omissions, and record what required human judgment. Advanced use of AI tools for research, requirements, analysis, and documentation is explicitly requested; no particular tool is specified.
Excel and performance analysis
In Microsoft Excel, analyze a small fictional launch-and-adoption dataset, calculate a few success metrics, and present a simple dashboard with one decision it supports. The posting requests Excel proficiency, dashboards, and performance and adoption monitoring.
Release and deployment readiness
Create a hypothetical user-acceptance checklist, release note, partner-readiness checklist, and post-launch feedback questions for one enhancement. These exercises reflect the stated testing, documentation, client and partner deployment, training, and release-readiness work.

Your preparation checklist

Map the GOE product context
The posting describes GOE as a B2B2C wealth platform serving global markets. Prepare a one-page map of possible advisory, retirement and private-wealth users and their needs; label assumptions rather than presenting them as facts about GOE.
Rehearse a product launch walkthrough
The role calls for experience defining and launching capabilities, MVPs or digital client experiences. Prepare one factual example covering discovery, prioritization, cross-functional decisions, launch, adoption and your specific contribution.
Draft a requirements sample
The role requires product requirements, user stories and acceptance criteria. As practice, choose a hypothetical digital investment enhancement and produce a short problem statement, prioritized stories, testable criteria and open questions.
Shape an AI-enabled use case
The posting asks for AI use cases, workflows, success metrics, risks and implementation tradeoffs, plus advanced AI-tool use. Prepare a hypothetical use-case brief and a separate, factual example of how AI tools improved your own product work, if applicable.
Evaluate an emerging-technology option
The team evaluates digital assets, tokenization and blockchain-enabled workflows. Prepare a concise hypothetical assessment of one option, including client value, APIs or data flows, custody and regulatory questions, and reasons not to pursue it.
Build a measurement example
The role defines success metrics and dashboards and calls for Excel proficiency. Prepare a small sample analysis showing adoption and performance measures, a dashboard sketch, and a decision the measures could inform.
Plan a regulated-market release
The posting covers client and partner readiness, training, user acceptance, release notes and post-launch feedback. Draft a hypothetical release checklist that identifies input needed from legal, compliance, risk, operations and investment teams.
Prepare questions for the employer
Bring questions about GOE's current product priorities, how regional and channel needs are prioritized, where AI opportunities face implementation constraints, and how the team measures adoption after deployment.

Availability last checked: 5 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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