Amber K.

Key Skills

Software

Don't disclose

Top Subject Matter

Generative AI regression testing automation (RAG)

Finance data pipelines for automated/AI-ready services

Knowledge agent, Multi agent creation, A2A communication

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

Function Calling

Text Generation

Question Answering

Fine-tuning

Evaluation/Rating

Computer Programming/Coding

Data Collection

Prompt + Response Writing (SFT)

Text Summarization

Classification

Segmentation

Polygon

Bounding Box

Entity (NER) Classification

Freelancer Overview

Backend Engineer who builds things that scale distributed systems, event-driven architectures, and now Agentic AI solutions. Currently at Target, I work at the intersection of backend engineering and Generative AI, designing multi-agent systems and high-throughput pipelines that power enterprise-scale operations. Previously spent 3 years at tiket.com, building the backend infrastructure behind one of Southeast Asia's largest travel platforms serving 17M+ users globally. What I care about: → Solving complex distributed systems problems → Making AI actually useful in production (not just demos) → Writing code that the next engineer will thank me for → Building systems that handle real scale, not theoretical scale Core Stack: Java · Go · Spring Boot · Kafka · Elasticsearch · Redis · GCP · Agentic AI · RAG · Multi-Agent Systems Education includes Bachelor of Computer Science, DIT University (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Function Calling.

Labeling Experience

Software Engineer — Target (Generative AI regression test automation platform)

Don't discloseText

Built and launched Target’s first Generative AI (GenAI) regression test automation platform using Retrieval-Augmented Generation (RAG) to support automated AI-driven test case generation. Implemented self-healing workflows to improve reliability of mission-critical distributed service testing and reduce manual QA workload. Designed the platform to evaluate and iterate AI-generated regression test behavior across releases and pipelines. • Enabled AI-driven generation of regression test cases • Added RAG-based retrieval for context grounding • Implemented self-healing mechanisms for failed tests • Reduced manual QA effort by 70%+ while improving release reliability

2025 - Present

Software Engineer — tiket.com (APIs and integrations supporting data pipelines)

TextFunction Calling

Participated in backend engineering work for a customer finance dashboard that supported downstream AI/automation use cases through high-performance APIs. Worked on secure integrations and data processing pipelines relevant to structured financial data that could be leveraged for ML/AI workflows. Focused on query optimization and multi-currency transaction handling to improve data readiness for analytics or automated decision systems. • Built high-performance APIs for large-scale customer finance use cases • Implemented secure bank integration handling encrypted and mapped data • Optimized reconciliation queries to improve processing efficiency • Managed multi-currency transaction conversion for global transactions

2022 - 2025

Education

Work History