Dakshitha is a full-stack engineer with 2+ years building distributed systems and operational excellence, shipping features faster through AI-native workflows.

Driven by a simple obsession: Customer problems, solved at scale.

Engineering toolkit for distributed systems and AI-native work.

Tech Stack

I work across backend services, data platforms, developer tooling, and AI integrations, with a focus on reliability, throughput, and shipping fast without compromising quality.

Languages & Frameworks

  • Java
  • Python
  • Spring Boot
  • React.js

Backend & Data

  • PostgreSQL
  • MySQL
  • Redis
  • Kafka
  • Kubernetes
  • REST APIs

Tools & Testing

  • Grafana
  • SonarQube
  • Docker
  • Git
  • Postman
  • JUnit
  • Mockito

AI / ML

  • LLM integration
  • RAG
  • Agentic systems
  • Fine-tuning
  • MCP
  • Context engineering

Selected engineering work.

Projects

A mix of side projects and production systems, across AI tooling, data platforms, and incident response, built end-to-end with a focus on reliability and developer leverage.

Experience & education

The path so far.

Worked across data platform reliability, cost optimization, AI tooling, and incident response.

2020 - 2024

B.E at R V College of Engineering

Electronics & Communication·. Bangalore

CGPA 8.18 / 10

Roles & communities

  • Student Placement Coordinator - helped coordinate campus recruitment and connect students with hiring teams.
  • CARV Access - member of the campus cinematography group; produced and edited short-form content for college events.
  • Rotaract Club - volunteer and member; participated in community service drives and student initiatives.

Sep 2023 - Feb 2024

Research Assistant Intern

Indian Institute of Science · Bangalore

  • Implemented an AES encryption layer for ADS-B aviation data, keeping system overhead within 5% across 50+ validation scenarios.

Mar - Sep 2024

Software Engineer Intern

A.P. Moller – Maersk · Bangalore

  • Built a tracking dashboard with 10+ REST APIs that eliminated 90% of direct database queries and cut debugging time by 60% per incident, with improved data security through controlled API access.
  • Refactored legacy code across 10+ microservices, resolved 300+ SonarQube smells, and reached 95% unit-test coverage.

Oct 2024 - Present

Associate Software Engineer

A.P. Moller – Maersk · Bangalore

  • Cut Kubernetes infrastructure cost by 23% - analyzed resource over-provisioning across data platform services for $48K+ annual savings ($577/day → $446/day).
  • Received a SPOT Award for resolving a production memory leak with a 300K+ message backlog; restored processing in 2.5 hours with zero data loss.
  • Built a RAG developer assistant (OpenAI LLM + ChromaDB) over 50K+ lines of legacy data-platform code, cutting new-engineer ramp-up time.
  • Reduced container-tracking MTTR by ~67% (~30 min → under 10 min) via 10+ structured triage slash commands automating the full SNOW-to-RCA pipeline across 17 production databases.
  • Built a location enrichment service processing 2M+ daily records, reducing data loss by 15% and unlocking real-time tracking for 10K+ shipments.
  • Onboarded Gnosis and OpenTech data providers, enabling 10K+ daily shipment updates.

About / Contact

Full-stack engineer focused on distributed systems and AI-native delivery.

I enjoy translating messy operational problems into reliable software, whether that's cutting infra cost, building RAG-based developer tooling, or shaping data pipelines that keep up with production scale. Open to product and platform engineering roles where I can own systems end-to-end.