Prathmesh Palande

Software engineering leader · Technical delivery

I help engineers deliver dependable systems.

With 8+ years across AI, data platforms, and cloud systems, I combine hands-on technical judgment with 3+ years leading teams and Scrum delivery. My focus is helping engineers make sound decisions, own outcomes, and improve how software ships.

View selected work LinkedIn
Practice 00 / Operating model Good systems let people own the work.

Set direction and expose trade-offs, delegate ownership, and keep feedback moving.

3+ years
leading technical teams and Scrum delivery
4–6
engineers led and onboarded on a delivery team
20
employees trained in Python through a cross-skilling program
30+
Computer Science Engineering / Artificial Intelligence and Data Science Engineering students at Vishwakarma Institute of Technology mentored through six-month paid internships and sponsored academic projects

01 / Selected work

Systems, decisions, and delivery.

Three cases showing context, scope, trade-offs, and outcomes—and what changed in the way the work moved.

Selected work 01 · Independent product · AI / mobile / cloud

Hearleaf

A consent-first mobile reader that turns photographed printed pages into progressively generated, locally cached audio in a voice the user controls.

Context
Printed pages are not equally accessible, while page images and personal voices demand careful handling.
Scope
Mobile capture, OCR review, and voice authorization through speech generation, playback, cloud delivery, and operations.
Role
Product owner and hands-on engineer across the mobile app, backend, speech pipeline, and infrastructure.
Constraints
Consent must precede page upload or voice use, and long-running jobs must survive retries without blocking playback.
Decisions
Default to reviewed on-device OCR, authorize voices before durable work, and generate immutable verified audio chunks.
Outcomes
Shipped a live Android product and simplified production from ten Cloud Run services to one CPU and one GPU service.
Lessons
Trust boundaries and recovery paths belong in the architecture, not in post-launch policy.
Visit Hearleaf Google Play

Under the hood

A reviewed path from page to playback

  1. 01Capture
  2. 02Review
  3. 03Authorize
  4. 04Generate
  5. 05Listen

Selected work 02 · Data-platform delivery · Team leadership

A shared operating model for data ingestion

Context
A growing ingestion estate was slowing delivery and producing inconsistent implementation patterns.
Scope
A multi-engineer team responsible for streaming and batch integrations on a data platform.
Role
Onboarded engineers and allocated work, balanced business priorities, and coordinated delivery.
Constraints
Improve maintainability and testing without pausing ongoing integrations.
Decisions
Introduced a shared loader pattern and made unit testing a team-wide quality practice.
Outcomes
Reduced one-off implementation patterns and raised test coverage across the ingestion estate.
Lessons
Standards create leverage when engineers can apply them independently.

Selected work 03 · Data and AI consulting · Delivery and modernization

Keeping delivery dependable through platform change

Context
Multiple data and AI engagements needed coordinated Scrum delivery alongside platform modernization.
Scope
Multiple consulting engagements spanning applied AI, data quality, and platform modernization.
Role
Led Scrum delivery with formal people-management responsibility and hands-on technical leadership.
Constraints
Migrate a production data platform while preserving dependable execution and active project delivery.
Decisions
Separated migration risk from feature delivery, clarified ownership, and moved workloads incrementally.
Outcomes
Improved execution resiliency while sustaining delivery across concurrent engagements.
Lessons
Migration plans work better when ownership, delivery risk, and operating behavior stay visible together.

02 / Experience

Teams, delivery, and technical depth.

Across roles, my scope has included hands-on engineering, team delivery, training, and formal management.

People and delivery leadership
Combined formal people-management responsibility with Scrum delivery and hands-on technical leadership.
Technical delivery
Led and onboarded a 4–6-person delivery team, allocating work and coordinating priorities.
Engineer enablement
Designed and delivered Python training for 20 employees at UBS.

Career progression

8+ years across products, platforms, and consulting.

  1. Tactable Intermediate Engineer

    Lead and onboard a 4–6-person delivery team while building data ingestion at 100M+ point scale.

  2. Altimetrik Senior Engineer

    Built observable delivery-scheduling services and modernized legacy APIs into FastAPI microservices.

  3. Fresh Gravity Consultant, Data Science and Analytics

    Led Scrum delivery across data and AI work, held formal people-management responsibility, and improved platform resiliency by 30%.

  4. Mastercard Software Development Engineer II

    Built authentication infrastructure and microservice integrations, test systems, and deployment automation.

  5. UBS Software Development Engineer I

    Built event-streaming systems and trained 20 employees in Python for organization-wide cross-skilling.

Beyond the org chart

Teaching, mentorship, and community stewardship.

Recorded technical sessions

Two long-form Faculty Development Program sessions delivered for Vishwakarma Institute of Technology, Pune.

Student development
Since 2022, I have mentored 30+ Computer Science Engineering / Artificial Intelligence and Data Science Engineering students at Vishwakarma Institute of Technology, providing six-month paid internships and sponsoring academic projects completed alongside their studies.
Vishwakarma Institute of Technology Alumni · Canada Chapter
Treasurer Vishwakarma Institute of Technology Alumni Association View official office-bearer listing

03 / About

How I work.

The work I keep choosing sits between systems and people: understanding a difficult problem, making the trade-offs visible, giving engineers useful context, and building delivery practices the team can own.

I do my best work when developing engineers, aligning technical work with business outcomes, and building delivery practices that do not depend on a single decision-maker.

I bring that approach from banking, payments, e-commerce, consulting, and an independent AI product, while staying close enough to architecture to coach sound technical judgment.

MBA in General Management · MS in AI and ML with Distinction · BTech in Computer Science Engineering

04 / Contact

Let’s build dependable systems and stronger teams.

I’m interested in teams working across AI, data platforms, cloud systems, or developer infrastructure where technical judgment and people development both matter.

palande.prathmesh@gmail.com GitHub LinkedIn