Jeevan Jyoti SrivastavaEngineering leadership · Backend & AI
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Jeevan’s field notesEngineering, with intent. / Est. 2012

Jeevan Jyoti Srivastava

Serious systems.
A curious mind.

Still asking “why?” Still building.

I lead engineering across backend platforms and AI products, staying hands-on with architecture, implementation and production operations.

View case studies View resume
Explore my engineering focus

A conversation has a state. A good system remembers it.

My work connects speech, learning flow and recoverable sessions.

Follow the request. Find the real bottleneck.

I work through the cache, the queue and the cost of each operation.

Leave the next engineer a better map.

Clear ownership, explicit decisions and the context behind the code.
Senior Engineering Manager · UOLOTurn to the work
01 / BackgroundJeevan,
in a few words.

I’ve moved into leadership.
I haven’t moved away
from engineering.

My career started in software development in 2012. Since then, I’ve worked on backend platforms, learning products, media delivery and real-time AI.

As a Senior Engineering Manager, I lead delivery and mentor engineers while staying involved in architecture and implementation. My work connects product workflows with the systems and tools that keep them running.

More about me

People, platforms & a lot of learning

A few stops along the way.

Follow the full story
  1. Oct 2020–present

    UOLO

    From platforms to voice AI.

    I joined as an SDE-3, then moved into engineering management while staying close to the architecture and code.

    SDE-3 → Senior Engineering ManagerStill writing this chapter
  2. Sep 2018–Sep 2020

    Dociety

    Making room to grow.

    I led the move from a monolith toward event-driven services, working through the scaling decisions along the way.

    AVP of TechnologiesRead this chapter
  3. Oct 2015–Aug 2018

    BitGiving

    Rebuilding the foundations.

    I led a platform re-architecture, from database design to planning the migration of existing work.

    Technology HeadRead this chapter

02 / From the workbench

Good questions.
Working answers.

Some things I’ve built, untangled and learned from. Open a case study for the decisions behind the work.

01 / Voice AI · Stateful orchestration

A voice tutor with an explicit learning journey.

Connecting real-time speech with curriculum flow, ordered playback and recoverable learner state.

Open field note
My responsibility
Designed the voice pipeline and the boundaries between teaching, assessment and conversation.
The key decision
Keep lesson progression in explicit learner state, with bounded agents for each learning activity.
What changed
Streaming speech, learning agents and recovery coordinated within one learning flow.
Architecture & hands-on engineeringInside the architecture

02 / Backend reliability · AWS

Finding the bottleneck before adding servers.

Tracing peak-hour failures through Redis lookups, request-path I/O and misleading capacity signals.

Open field note
My responsibility
Led the investigation from production request behavior to infrastructure signals.
The key decision
Replace repeated cache scans and move expensive processing into background workers.
What changed
Cheaper request lookups, separated heavy processing and a repeatable capacity investigation process.
Platform architecture & performance leadRead the case study

03 / Data access · Asynchronous workloads

Keeping expensive work out of the request path.

Reducing unnecessary data work and separating background jobs from latency-sensitive APIs.

Open field note
My responsibility
Reviewed data access and execution patterns across platform workflows.
The key decision
Use lighter reads and bounded concurrency; make background processing an explicit boundary.
What changed
Reusable practices for data reads, asynchronous jobs and evidence-based cache sizing.
Platform architecture leadRead the case study

04 / Media infrastructure · Content delivery

Adaptive video for inconsistent connections.

Designing the path from source video to adaptive playback across bandwidth and device constraints.

Open field note
My responsibility
Designed the media publishing and delivery architecture for a learning platform.
The key decision
Separate encoding from durable storage and deliver adaptive HLS renditions through a CDN.
What changed
An automated publishing path with multiple renditions, independent of application request capacity.
Platform & media delivery architectureRead the case study
Explore all 10 case studies

03 / Working notes

A few things
I come back to.

  1. 01

    Start with the evidence.

    I want to understand where the time goes, what state changed, and which assumption stopped holding.

  2. 02

    Make the boundaries clear.

    I look for explicit ownership of state, decisions and recovery—especially when an AI model is involved.

  3. 03

    Leave the reasoning behind.

    A system should be understandable to the next engineer who has to change it or investigate an incident.

04 / Say hello

Have a role
in mind?

I’m interested in Staff and Principal engineering roles where I can stay close to the systems and the code.

Get in touch [email protected]