Skip to the content
ABOUT

The long way here.

I build AI products that make complex systems usable.

Four builds are on this site, covering household utility bills, model selection, investor research, and LLM evaluation.

I am looking for an AI product role where strategy, technical judgment, and real user consequences meet.

Present day · 2026
Teja Padala in a navy suit outside a brick building.
Chronology begins
I began in civil engineering. At NJIT, engineering management—and electives in analytics and software engineering—became my bridge into technology. From 2017 through mid-2024, I built cloud and data systems across two regulated client environments, co-founded a technology consulting company, and used business school to move closer to product, venture capital, and applied AI. The disciplines meet now, in the work I build.
2014–2016 Engineering

Civil engineering taught me to read systems. Engineering management opened the path into software.

At NJIT, analytics and software-engineering electives turned that systems mindset toward technology. The underlying questions stayed familiar: how complex systems are specified, connected, tested, and trusted.

I completed a BTech in Civil Engineering at GITAM in 2014, then an MS in Engineering Management at NJIT in 2016. At NJIT, electives in analytics and software engineering gave me a practical route into technology. The domain changed, but the systems thinking carried forward: understanding dependencies, finding failure points, and building structures people could rely on.

Single track. One discipline, learned as a way of reading systems.
2014 BTech Civil Engineering, GITAM.
2016 MS Engineering Management, NJIT.
2017–2024 Hexaware Technologies Employer

From 2017 through mid-2024, I worked across two regulated client environments where what we built had to remain explainable later.

One employer, two sequential client environments: Fannie Mae, then Rite Aid. Mostly AWS. The organizations ran machine learning; I was helping build the data foundations beneath it.

In April 2017 I joined Hexaware Technologies and was placed on the Fannie Mae account, where I spent five and a half years as a software technology consultant. Hexaware was my employer; Fannie Mae was the environment I worked in. Consulting into a regulated institution teaches a particular discipline, because everything you build has to be explainable later.

Most of that work was on AWS. For a stretch I sat on the data mart team, building and testing the ETL that fed the business intelligence teams, bringing structured and unstructured sources into a shape people could work with. The organization ran machine learning. I was not building models. I was helping build the data foundation beneath them.

In 2021, still on the account, I completed a master's in information technology at the University of the Cumberlands while working full time. It was the first stretch where what I studied and what I did all day pointed the same direction.

One employment spine. Client accounts sit inside it; a founder track starts inside it too.
2017–2022 Client account Fannie Mae — software technology consultant. AWS, data marts, and the ETL feeding downstream BI and ML teams.
2021 MS Information Technology, University of the Cumberlands — completed while working full time.
2023–mid-2024 Client account Rite Aid — lead software consultant. Pharmacy operations, AWS, ML-enabled operational workflows in another regulated environment.
2022–2024 The TekWinn Company Concurrent

A consulting company built alongside the full-time role. $1.8M revenue by 2024.

Founding partner and product lead, built while the Hexaware employment continued — this track overlaps the last two years of that spine, it does not replace it.

In January 2022 I co-founded The TekWinn Company as founding partner and product lead. It was a technology consulting company that I developed while continuing my full-time role at Hexaware. By the time I stepped away in 2024, TekWinn had generated $1.8 million in revenue.

A year into that, Hexaware moved me to the Rite Aid account as lead software consultant: pharmacy operations across a distributed network, ML automation on AWS, another regulated environment. It moved me closer to ML-enabled operational workflows rather than only the infrastructure beneath them.

In July 2024 I left both to start the MBA full time. I had been circling business school for a while and wanted to give it my whole attention.

Two tracks run at once. Neither replaced the other.
Concurrency

Two tracks, one period — then they converge.

201720192021202320252027
Employment
Founder
Education
Product · venture

Bars are drawn from the dated record. Where they overlap, the work overlapped. The 2021 marker is a completion date, not a duration claim.

2024–2026 The bridge

An MBA is usually described as a pivot. Mine was closer to a bridge.

Kenan-Flagler added product judgment, deeper commercial reasoning, a venture perspective, and repeated practice moving ideas between technical and business audiences.

I arrived with seven years of systems and data work and two years of running a company. Kenan-Flagler added product judgment, deeper commercial reasoning, a venture perspective, and repeated practice moving ideas between technical and business audiences without losing them along the way. Both chapters below happened inside those two years.

Teja seated on a low wall facing the columned façade of Louis Round Wilson Library at UNC.
2026 MBA, UNC Kenan-Flagler.
Teja with classmates in a Kenan-Flagler classroom in front of a projected team presentation.

A course team presentation at Kenan-Flagler, with the classmates I worked with on it. Much of the bridge was practice at moving an argument between audiences.

Summer 2025 EssilorLuxottica Inside the bridge

Twelve weeks in Dallas, two workstreams: diagnosis, then a proof of concept.

A hypothesis-led diagnosis of where operational escalations originate across the purchase-to-delivery workflow, and a returns and delivery-risk proof of concept built with three data scientists.

Twelve weeks in Dallas across two workstreams. The first was a hypothesis-led diagnosis of where operational escalations originate across the purchase-to-delivery workflow, and recommendations involving SLA triggers, standard operating procedures, and data architecture.

The second was a returns and delivery-risk proof of concept proposed by Teja and developed with three data scientists based at the Paris headquarters using Databricks ML on Azure. It demonstrated value on one B2B-vendor use case and informed a broader rollout initiated afterward.

A proof of concept, not a deployment.
2025–now Inside a fund

An internal research need became a product.

The fund had a long list of prospective investors and no dependable way to decide who deserved attention first. Building that ranking workflow became the Investor Intelligence Platform.

In August 2025 I joined the investment team at Excelerate Health Ventures, a seed and Series A fund investing in B2B pharma tech. I spent a year there and continue to work with them part-time.

Alongside investment research, an internal workflow need became a product. The fund had a long list of prospective investors and no dependable way to decide who deserved attention first, and building that ranking workflow became the Investor Intelligence Platform.

Research and building start happening in the same week.
2026–now Building

Four builds, one shape: evidence trapped in a form that makes the next decision harder.

Household bills Model selection Investor intelligence LLM evaluation

Four builds now carry that accumulated experience into different domains: household bills, model selection, investor intelligence, and LLM evaluation. They share a common shape: important evidence trapped in a form that makes the next decision harder.

I am also developing Profoundly, an interview series about how AI changes people's work, judgment, identity, and direction.

All tracks arrive here.
Teja standing on a snow-covered ridge in Colorado with mountains behind him.

Denver, and the reason the mountains keep showing up.

Convergence

I want to bring this combination of systems thinking, product judgment, and hands-on building into a team working on consequential AI products.

The problems that hold my attention are the ones where models shape meaningful decisions, where the evidence behind an output stays inspectable, where technical and product tradeoffs are genuinely in tension, and where being honest about uncertainty makes the product better rather than weaker.

That is the work I am best equipped for, and the work I want to keep doing.

Outside the work
Teja in a tan blazer at an evening event.
Teja celebrating with both arms raised at a 5K finish line in Denver.

Denver, a 5K finish.

Denver is where the running, the mountains, and the building all happen in the same week.

A Colorado valley with a river, wildflowers, and mountains, with Teja standing small in the landscape.
A Colorado valley with a river, wildflowers, and mountains, with Teja standing small in the landscape.
Contact

Product work

If you are hiring or building with AI and think my experience could help shape the product, strategy, or execution, write to me. I will send a résumé focused on that work.

Portfolio inquiry

Profoundly

If AI changed your work, your judgment, your sense of identity, or your direction, I would like to talk to you for the interview series.

Profoundly conversation

tejaswar.padala@gmail.com

{{ activeSpan }} {{ activeLabel }}
Timeline anatomy

One chronology, four tracks, honest overlap.

Persistent rail (desktop)

Thirteen rows, one per entry in the chronology data — the nine career and chapter spans plus all four degrees — fixed at mid-viewport left. An amber fill tracks scroll position through the whole chronology; a cyan pulse gives the rail life at rest. Degrees and concurrent chapters are indented off the spine in green rather than inserted into the career sequence.

Active-span logic

Every milestone carries a named anchor id. The active row is the last anchor above 50% of the viewport whose id exists in the chronology data — no index arithmetic, so inserting a degree cannot misalign the rail. The opening is its own explicit state. Upward scroll reverses by the same rule instead of undoing a triggered animation.

Concurrency

Employment, founder, education, and product/venture are separate lanes on a 2017–2027 axis. Bars are positioned from dated facts, so overlap is drawn, not implied. The 2021 master's is a point marker because only its completion date is known.

Mobile chronology

The rail is replaced, not shrunk: a sticky current-era bar with a 2px progress line, and a 48px-row expandable chronology sheet that jumps to any span.

Motion inventory

  • Ambient at rest: rail pulse, present-day marker breath, hero portrait micro-scale. Three layers, no more.
  • Scroll-authored: rail fill, clause sweep, five image apertures, lane bars, convergence lines.
  • Everything is computed from element position each frame, so reverse scroll is exact.
  • The loop stops on tab hide and skips elements outside the viewport band.
Crop and focal-point inspector

Every crop keeps its subject.

Source frame: primary portrait.

01 · 1290×1270 · frame 1:1, focal 50% / 42%. Near-square source kept near-square; no 4:5 narrowing. Entry: centre aperture.

Source frame: UNC colonnade.

06 · 5712×4284 · displayed contained, zero crop. The person-to-building scale is the content, so nothing is cut. Entry: curtain wipe.

Source frame: 5K finish.

04 · 4284×5712 · frame 3:4, focal 50% / 62%. Raised arms and legs both inside frame; bottom not cut. Entry: reveals upward from the ground.

Source frame: editorial portrait.

02 · 3213×5712 · native ratio kept, focal 50% / 30%. Head and body whole. Entry: image slides inside a fixed aperture.

Source frame: Colorado winter ridge.

05 · 4032×3024 · band recomposed in V2.1.1. Stated accurately: the 4:3 source is cropped vertically on wide desktop apertures — a 420px band across the desktop column shows roughly 55–65% of the frame height at 1440 and 1280, so the vertical crop is real. What keeps the subject safe is the constrained focal range (object-position Y 10% → 6% only) together with the top-origin reveal, which hold Teja's full head inside the visible band at reveal entry, reveal midpoint, settled state and reverse-scroll midpoint, at 1280 and 1440, and at 390×844 where the 260px band is very nearly uncropped. V2's 44% → 53% drift cut the head and was rejected.

Source frame: Kenan-Flagler course team.

07 · promoted in V2.1 · min(560px, 45vw) desktop, full content width mobile, object-fit contain so the whole 4:3 group survives, curtain reveal, caption below · truthful collaboration caption, never dominant.

One responsive moment, two sources

Source frame: Colorado valley, wide.

08 wide · desktop only · 4:3 aperture opening from a centre horizon band.

Source frame: Colorado valley, vertical.

09 vertical · mobile only · 3:4 aperture, same beat. Never adjacent to 08 in the journey.

03 relaxed portrait is held out: the coda already has a human lead and a second portrait would turn it into a gallery.

Reading depth

Scan, story, full detail — same era, three depths.

Depth 1 and 2 are always visible. Depth 3 opens from a 44px button and is reachable by keyboard on every device. No fact lives only in a hover state.

1 · Scan 2017–2022 · Regulated systems

Five and a half years where everything built had to be explainable later.

≈ 6 seconds. Recruiter-speed read.

2 · Story

Most of that work was on AWS, much of it on the data mart team. The organization ran machine learning. I was not building models. I was helping build the data foundation beneath them.

Always on screen, under the scan line.

3 · Full detail

In April 2017 I joined Hexaware Technologies and was placed on the Fannie Mae account, where I spent five and a half years as a software technology consultant. Hexaware was my employer; Fannie Mae was the environment I worked in… plus the ETL and 2021 master's paragraphs in full.

Opens in place. Verbatim canonical copy, nothing paraphrased upward.

Interface sentences I wrote (not in the canonical copy)

  • “Civil engineering taught me to read systems. Engineering management opened the path into software.”
  • “Five and a half years where everything built had to be explainable later.”
  • “A consulting company built alongside the full-time role. $1.8M revenue by 2024.”
  • “Twelve weeks in Dallas, two workstreams: diagnosis, then a proof of concept.”
  • “An internal research need became a product.”
  • “Two tracks, one period — then they converge.” and the four lane labels.
  • “Denver is where the running, the mountains, and the building all happen in the same week.”
  • Contact invitations for product work and Profoundly, and the short track notes beside each era.

Each is a compression of supplied copy. None adds a metric, a client name, a deployment claim, or a date that is not in the source.

Rejected patterns

Seven treatments considered and refused.

Static editorial article

Reads well at leisure, tells a recruiter nothing in 60 seconds, and cannot show that two tracks ran at once.

787-word paragraph wall

The canonical copy is the authority, not the layout. Printing it in one reading path breaks the 120-word viewport gate.

Generic card grid

Equal cards flatten chronology into a menu. Nothing accumulates, nothing overlaps, nothing converges.

Hobbies gallery

Nine photographs as a mosaic turns evidence into decoration. The coda keeps three, each doing a job.

2014
2017
2021
2024
2026

Desktop rail squeezed onto mobile

6px labels and 20px targets. Replaced with a sticky era bar and a 48px-row chronology sheet.

Illustration of a rejected crop that cuts the head.

Face-cutting hero crop

A fashionable narrow band across the portrait removes the person. Every frame in the journey keeps its subject whole.

Uniform fade-up reveals

One easing applied to everything says nothing about the content. Each image entry here is chosen for its narrative role.