Software Engineer

Manikanta Illuri

Building intelligent systems at the intersection of AI and Cloud infrastructure.

About

Crafting software that makes a difference.

I'm Manikantanagasai Illuri—I go by Manikanta—a recent Computer Science graduate from UC Santa Cruz with a passion for building intelligent, scalable systems at the intersection of AI and cloud infrastructure. My work focuses on leveraging LLMs, retrieval pipelines, and modern cloud platforms to solve real-world engineering challenges.

From building AI-powered observability tools to architecting multi-agent systems that won first place at UC Berkeley's AI Summit, I thrive on tackling complex problems with elegant, production-ready solutions. My experience spans the full stack—from database migrations and API integrations to ML model serving and DevOps automation.

When I'm not coding, I'm exploring emerging AI technologies, earning professional certifications, and contributing to the evolution of intelligent systems that make developers' lives easier.

Education

Academic background.

University of California, Santa Cruz

Baskin School of Engineering

Bachelor of Science in Computer Science

Minor in Technology & Information Management

Graduated: June 2025

Experience

Where I have made an impact.

Software Engineering Intern

CloneTab Inc. • Remote

June 2025 – Present

Built retrieval-based AI assistant over metrics + logs by integrating telemetry APIs (Prometheus/OpenTelemetry) with custom retrieval/ranking pipelines, enabling natural-language on-call and debugging workflows.
Improved reliability and reduced latency by enforcing context budgeting, intelligent chunking, and inference controls (timeouts/retries), stabilizing responses on highly variable log volumes.
Led full Oracle XE → PostgreSQL migration: translated schemas, optimized queries/indexes, and validated correctness/performance with before/after benchmarking.

Software Engineering Intern

Cloudbrink Inc. • Sunnyvale, CA

June 2024 – September 2024

Developed BigQuery log analytics pipeline supporting natural-language queries (NLQ), replacing manual log review with structured retrieval + summarization.
Increased throughput and cut query cost/latency by building Python preprocessing layer (normalization, filtering, schema extraction) for high-volume JSON alert data.
Reduced SRE investigation time ∼50% through automated concise incident summaries (root-cause hints, top offenders, time windows).

Data Engineering Intern

Innominds Inc. (HCCC CARS Project) • Livermore, CA

June 2023 – September 2023

Designed and implemented enterprise document ingestion + search pipeline: automated metadata extraction and indexing into Elasticsearch for fast keyword + filtered retrieval.
Added role-based access control (RBAC) to scope search results by user permission, strengthening security while preserving discoverability.

Projects

Selected work.

1st Place @ UC Berkeley: ConstructionAgent – Emergent Coordination with LLM-Based Agents

Won 1st place at AI Multi-Agent Competition, Agentic AI Summit (UC Berkeley, 2025). Architected multi-agent system where LLM agents develop emergent language and coordinate complex construction tasks through natural-language interaction with no pre-defined protocols.

LLMMulti-Agent SystemsPythonNatural LanguageAI

ImageGen – Full-Stack ML Image Generation & Captioning

Built end-to-end web application (React frontend + Flask backend) integrating PyTorch models for image captioning, editing, and text-to-image generation. Implemented user upload/prompt workflows with efficient model serving and responsive UI.

ReactFlaskPyTorchMLFull-Stack

Certifications