I am a Senior Software & Machine Learning Systems Engineer at Adobe (Santa Clara, CA), working on core Generative AI platforms and multi-tenant LLM agent runtimes for Adobe Brand Concierge (and previously Adobe Journey Optimizer). My work spans end-to-end agent orchestration (PydanticAI, Model Context Protocol), grounded RAG with sub-second neural cross-encoder rerankers, automated prompt/program optimization (GEPA, DSPy), and high-throughput streaming serving infrastructure.
Prior to Adobe, I earned my Master’s in Computer Science from the University of California, Irvine (GPA: 3.94/4.00), where I researched in-context learning, prompt robustness, and chain-of-thought reasoning in LLMs under Dr. Sameer Singh. I completed my B.Tech at the Indian Institute of Technology, Kharagpur (Electrical Engineering with a minor in Computer Science;GPA: 9.04/10.00; All India Rank 481 in IIT-JEE Advanced & AIR 120 in JEE Mains).
Earlier in my career, I engineered real-time IoT vehicle telemetry microservices and compliance systems at TruckX, built search autocomplete and analytics microservices at Adobe TechComm (2018–2021), and conducted cloud performance research at Adobe Research’s BigData Experience Lab (2017), winning the Best Intern Project Award and co-authoring US Patent US20190354388.
Outside of engineering, I am an avid sports enthusiast with a strong passion for badminton, a keen follower of equity markets, and a lifelong believer in forming rigorous hypotheses and validating them with empirical data.
Stan Weinstein Stage 2 sector momentum scanner, market intelligence briefings, portfolio audits, and book-length company monographs for NYSE/NASDAQ & NSE/BSE.
Structured travel dossiers, route planning, logistics matrices, and field research across destinations.
Abstract & BibTeX
@inproceedings{mekala2024echoprompt,
title={EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-Context Learning},
author={Mekala, Rajasekhar Reddy and Razeghi, Yasaman and Singh, Sameer},
booktitle={Findings of the Association for Computational Linguistics: NAACL 2024},
year={2024},
url={https://arxiv.org/abs/2309.10687}
}
Abstract
- Demand-paged agent context with revocable tool capabilities
- Evidence-linked causal evolution of typed agent manifests
- Anti-collusion dual optimization for judges and agents
Adobe Brand Concierge — Generative AI Platforms & Agent Systems
- Built agent orchestration, tool configuration, and runtime infrastructure for multi-tenant workflows.
- Worked on grounded source attribution and CPU-based inference and reranking services.
- Developed evaluation and prompt-optimization infrastructure for agent systems.
| Date | Update |
|---|---|
| Mar 13, 2024 | Our paper “EchoPrompt” accepted to NAACL 2024. |
| Jun 20, 2023 | Graduated with M.S. in Computer Science at UC Irvine (GPA 3.94/4.00). |
| Dec 05, 2022 | Attended EMNLP 2022 in Abu Dhabi to present SNOOPY. |
| Oct 06, 2022 | Published first NLP system demonstration paper (SNOOPY) at EMNLP 2022. |
Experience
- Jun 2023–Present: Software Engineer, Generative AI Platforms & Agent Systems, Adobe Inc. (Santa Clara, CA)
- Jul 2022–Jun 2023: Software Engineer, TruckX Inc. (Sunnyvale, CA)
- 2021–2023: Graduate Student Researcher & GTA, UC Irvine (UCI NLP Lab)
- 2018–2021: Member of Technical Staff 1 & 2, Adobe Inc. (Bangalore)
- Summer 2017: Research Intern, Adobe Research (BigData Experience Lab)
Education
- M.S. in Computer Science, UC Irvine (2021–2023) • GPA: 3.94/4.00
- B.Tech in Electrical Engg. (CS Minor), IIT Kharagpur (2014–2018) • GPA: 9.04/10.00
Key Honors
- Adobe Spot Award (2021) & Special Contribution Award (2020)
- Best Intern Project Award (2017), Adobe Research
- IIT-JEE Mains AIR 120 & JEE Advanced AIR 481 (2014)
- KVPY Fellowship & IMO Training Camp (2013)
- Portfolio Research Desk — Stage 2 & Dossiers
- Travel Research Desk — Trip Monographs
- 2048 in React — Interactive Web Game
- GitHub (@rajasekharmekala)
- LinkedIn Profile
- X (@rajasekhar_732)
- Google Scholar Profile