# Surya Teja Reddy Dwarampudi

> SDE2 · SCALER AI LABS · Bengaluru, IN · available · 2026.
> Contact: hi@itssurya.com.
> Currently: building RL environments, authoring SWE-Bench tasks, wiring up data pipelines, shipping internal AI tools, shipping voice agents, tuning sub-ms search.

## About

**Engineer. Builder. Curious about how things scale.**

I work on **AI infrastructure**, **realtime systems**, and the internal tools companies live inside. Started as an intern at Scaler in 2023; full-time soon after. Now at **Scaler AI Labs** — founding team, building RL environments, eval tasks (SWE-Bench, Terminal-Bench), data pipelines, and the AI tooling the research team runs on.

I care about the unglamorous parts: the call that answers in 800ms, the search that returns under a millisecond, the CRM your team doesn't dread opening. If a product feels effortless, someone did the hard work under the hood. That's the part I enjoy.

Outside work: a first-principles thinker, occasional hackathon winner, and Bengaluru-based optimist about the next decade of software.

- **50+ eng** — org I build with
- **$10M+** — revenue generated
- **5.4 cr+** — annual costs cut
- **9.8/10** — cgpa · top 1%

## Experience

### Software Engineer II — Scaler AI Labs (current)
_Oct 2025 to present · Bengaluru_

- **RL environments** for computer-use agents — high-fidelity GUI simulation so frontier models can learn to operate a desktop. Single-agent and multi-agent.
- **SWE-Bench & Terminal-Bench tasks**: authoring and curating evals that grade agents on real software-engineering work.
- **Data pipelines** turning messy real-world traces into training-grade data.
- **Internal AI productivity tools**: the stack the research team uses day-to-day.
- Partnering with **3+ global AI research labs** to benchmark model performance. Mentoring junior engineers across workstreams.

### Software Engineer I — Scaler by InterviewBit
_Jul 2024 to Jan 2026 · Bengaluru_

- **Real-time AI Voice Agent (IVR)**: low-latency calling platform on Gemini + Deepgram (ASR) + ElevenLabs (TTS) handling **15+ concurrent** sales calls at **<800ms** latency.
- **Sales AI Simulator**: internal training platform where AI agents role-play as prospects, so reps can practice pitches before real calls.
- **Automated Call Intelligence**: compliance pipeline auditing **10K+ calls/month** across sales and support. LLMs flag compliance issues and surface coaching insights.
- **CRM Cost Optimization**: architected in-house CRM replacing LeadSquared. Cut annual costs by **90% (₹5.4Cr+)** with **100% adoption** in 4 months.
- **High-Scale Search**: advanced filtering engine on **3M+ leads** serving **100K+ queries/mo** at sub-ms latency (ElasticSearch + tuned indexing).
- **Zero-Conflict RBAC** across 12+ modules · scalable monorepo (Turbo + Next.js) · no-code workflow builder on React Flow · double-digit concurrent A/B tests.

### Software Engineer Intern — Scaler by InterviewBit
_Mar 2023 to Jul 2024 · Bengaluru_

- **Needle-Mover Award**: reduced mentor no-shows from **11% → 3%** via a custom scheduling feature on Ruby on Rails + React.
- **Self-serve admin tools** cut weekly support tickets by **60%** (30→12), saving **100+ eng-hours/yr**.
- Optimized the Article page with lazy-loading + server-side pagination, serving **500K+ MAU** with improved core web vitals.

### Full-Stack Developer Intern — SCSET · Bennett University
_Sep 2022 to Jan 2023 · Greater Noida_

- Built interactive admin dashboards in Django to visualize inter-school activity data.

## Projects

### 01. Real-time voice agent for sales calls
_flagship · 2025_

A low-latency calling platform that picks up, holds a real conversation, and books meetings. Built on Gemini + Deepgram + ElevenLabs, tuned for 15+ concurrent calls without sounding like an IVR.

**Stack:** Gemini, Deepgram, ElevenLabs, Node.js, Redis, WebRTC

**Role:** Lead engineer · architecture, latency, orchestration

- **<800 ms** — avg latency
- **15+** — concurrent calls
- **24/7** — uptime

### 02. In-house CRM that replaced a ₹5.4 Cr vendor
_scale · 2024_

Architected the in-house CRM that retired LeadSquared in 4 months. Zero-conflict RBAC across 12+ modules, sub-millisecond filtering on 3M+ leads, a no-code workflow builder, and double-digit concurrent A/B tests from day one.

**Stack:** Next.js, TurboRepo, ElasticSearch, PostgreSQL, React Flow, Kafka

**Role:** Frontend architecture · search infra · RBAC · workflow engine

- **90%** — cost reduction
- **3M+** — leads indexed
- **100%** — team adoption

### 03. Call audit pipeline at 10K calls/month
_compliance · 2024_

Built the automated call-intelligence layer. Every sales and support call gets transcribed, classified, scored against a compliance policy, and fed back as a coaching nudge. LLMs catch the issues a manual QA pass tends to miss.

**Stack:** Python, FastAPI, OpenAI, AWS MSK, Postgres, OpenSearch

**Role:** Pipeline architecture · LLM prompting · review tooling

- **10K+** — calls/month
- **94%** — precision flagging
- **3 d** — review-to-prod loop

### 04. Sales AI simulator: agents that role-play as leads
_training · 2025_

An internal training arena where AI agents role-play as buyers across personas, objections, and stalling tactics. Reps practice live, get scored, and walk into the real call already warmed up.

**Stack:** Gemini, TypeScript, Next.js, Postgres, pgvector

**Role:** End-to-end · prompts, eval harness, frontend

- **6 wks** — rep ramp-up cut
- **40+** — persona library
- **5x** — practice volume

### 05. Founding work at Scaler AI Labs (current)
_current · founding · 2025–_

RL environments (single + multi-agent) for computer-use agents, SWE-Bench and Terminal-Bench eval tasks, data pipelines, and the internal AI tools the research team runs on. Founding team — started Oct '25 inside Scaler, workspace spun out Apr '26.

**Stack:** Python, TypeScript, Playwright, Docker, RL · PPO/GRPO

**Role:** IC SDE2 · mentor to junior eng across workstreams

- **50+** — engineers in org
- **3** — research partners
- **7** — workstreams

## Now — Scaler AI Labs · founding team

Splitting the week across RL environments for computer-use agents, authoring SWE-Bench and Terminal-Bench eval tasks, the data pipelines that feed them, and the internal AI tools the research team relies on. Partnering with 3 global AI research labs — the bar keeps moving, which is the fun part.

- **reading:** DeepMind's SIMA paper, again. This time for the eval harness.
- **learning:** PPO tuning + process supervision for browser-use tasks.
- **listening to:** A lot of Khruangbin while the GPUs spin.

## Skills

- **Generative AI:** **Gemini**, **OpenAI**, **Anthropic**, **Computer-use agents**, **RL (PPO/GRPO)**, LangChain, Deepgram (ASR), ElevenLabs (TTS)
- **Languages:** **TypeScript**, **Python**, JavaScript, Ruby, C++, SQL
- **Frameworks:** **Next.js**, **React**, Node.js, FastAPI, Ruby on Rails, GraphQL
- **Libraries:** Redux / RTK Query, React Flow, Prisma, Sentry, TurboRepo
- **Infrastructure:** **AWS**, ECS / EC2 / RDS, OpenSearch / Elastic, MSK · Kafka, Docker, Jenkins, Redis
- **Patterns I love:** Event-driven, RBAC / Zero-conflict, A/B + feature flags, Workflow engines
- **Learning next:** Rust, native CUDA, iOS / Swift
- **Currently learning:** **Process supervision**, **Eval design**, WebGPU

## Links

- LinkedIn: https://linkedin.com/in/suryateja222
- GitHub (personal): https://github.com/surya-teja-222
- GitHub (work): https://github.com/suryateja-7
- LeetCode: https://leetcode.com/suryateja222
- Résumé: https://drive.google.com/uc?export=download&id=1L8aAJTZd48JKFa-fypYdiR7vG4X_Wtwu