01
Backend & platform
APIs, workers, modular monoliths, service gateways, database-facing systems, and deployment-friendly tooling.
GoPostgreSQLDockerShell
Technical Lead · Backend Engineer · Data Scientist · Go-first
Muhammad Haykal Kamil.
I build systems that ship.
I'm Kamil, a technical lead, backend engineer, and data scientist with 3+ years across software engineering, data, and AI, plus hands-on technical and teaching work dating back to 2020. I lead cross-functional delivery, build Go services and full-stack TypeScript products, and ship applied AI—from classical ML and document intelligence to production LLM-powered tools.
103
repositories contributed to
3,322
commits in evidence snapshot
44
repositories using Go
3+ yrs
software, data & AI experience
01 / Focus
Engineering across the product stack.
My work clusters around reliable Go services, internal developer platforms, database tooling, and product interfaces in TypeScript. I also build applied AI/ML systems—from LLM-powered products and document intelligence to deep-learning workflows and cloud-hosted model pipelines.
02
Developer tools
CLIs, schema tooling, code generation, lightweight DB interfaces, framework experiments, and workflow automation.
CLICodegenHTMXMake
03
Full-stack & AI
Modern TypeScript products and AI-enabled applications, including agentic LLM workflows, document understanding, model integration, and deep-learning experimentation.
TypeScriptNext.jsTanStack StartLangGraphPython
02 / Experience
Production systems, AI, and data work.
A condensed professional timeline cross-checked against my formal CV and LinkedIn experience history. The emphasis is progression, scope, and outcomes; private implementation details and repository identities remain intentionally omitted.
Nov 2023 — Present
REDIKRU · Full-time
Jakarta · Hybrid
Jakarta · Hybrid
Backend → Data & AI → Technical Leadership
Expanded from core backend ownership into applied data/AI and technical leadership while continuing to contribute across production systems, MVP delivery, and R&D.
Technical Lead
Lead a 4-member cross-functional team delivering full-stack MVPs and R&D initiatives, oversee Data & AI engineering alongside backend work, and coordinate technical alignment, task distribution, and delivery.
Data Scientist
Gather and analyze business data, build and deploy ML models, work with LLMs/VLMs through prompting and fine-tuning, and deploy data/ML solutions with AWS SageMaker and Lambda using Python and SQL.
Back End Developer
Core backend engineer across production products from MVP to live deployment. Built Go/Gin server-worker systems, TypeScript services, a B2C maritime job-matching platform, and B2B ERP systems covering crew, vessel, contracts, LMS, attendance, and payroll.
Delivery: 5 web ERP products + 2 mobile ERP applications for client companies; Clean Architecture, TDD, API versioning, database architecture, Redis caching, and Asynq background processing.
Additional reported impact: reduced production costs by 70% through LLM API integrations and improved team productivity through ML, data engineering, and workflow optimization.
GoGinTypeScriptERPRedisAsynqAWS SageMakerAWS LambdaLLM / VLMPythonSQLMetabase
Mar 2026 — Jun 2026
Technova Solusi · Freelance
Backend Engineer
Backend Engineer
Telecom provisioning & integration microservice
Built and maintained a Go microservice for ISP service provisioning, order management, and customer operations, acting as an integration layer between internal systems and external platforms. Designed a shared business layer serving REST and gRPC clients with Clean Architecture / Port & Adapter principles.
Integration scope: 10+ external APIs spanning payments, OIDC authentication, media/services, WhatsApp omnichannel, and telecom providers; event-driven processing with Kafka, Redis-backed OTP/token workflows, signed webhook verification, and TM Forum-aligned service APIs.
GoGingRPCProtobufMariaDBGORMRedisApache KafkaKeycloak / OIDCREST APIsClean ArchitectureTM Forum
Apr 2025 — Oct 2025
Technova Integrasi Solusi · Freelance
AI Engineer · Remote
AI Engineer · Remote
From LangGraph prototype to production Go AI service
Built an AI chatbot agent in Python with LangGraph, then migrated and reimplemented the solution in Go for production readiness. Delivered the AI solution end-to-end from experimentation through implementation and collaborated directly with client stakeholders.
LangGraphPythonGoAI AgentsLLM APIClient Delivery
Jun 2023 — Jul 2023
bank bjb · Internship
DPLK Operations · On-site
DPLK Operations · On-site
Data visualization in financial operations
Supported DPLK operational work through data visualization and website review, adding financial-services exposure to an engineering and data-focused background.
Data VisualizationAnalysisWebsite Review
Feb 2021 — Feb 2023
Telkom University
Teaching, laboratory & NLP roles
Teaching, laboratory & NLP roles
Teaching foundations and NLP research
Served across programming, data structures, software testing, object-oriented programming, and NLP teaching roles. Guided classes in Go, Java, C++, Python/NLTK, Maven, Jira, and Katalon; also coordinated OOP practicum assistants before supporting an NLP course as an assistant lecturer.
Leadership foundation: coordinated practicum responsibilities and guided multiple classes before moving into professional engineering leadership.
GoJavaC++PythonNLTKNLPSoftware TestingTeaching
Jun 2021 — Jan 2022
eKopz · Internship
Back End Developer
Back End Developer
Early production backend experience
Worked on backend systems for a digital cooperative platform, including API development and database-oriented engineering for financial-service workflows.
BackendAPI DevelopmentDatabase Design
03 / Research
Published work in Indonesian NLP.
My undergraduate research applied Transformer-based deep learning to Indonesian word syllabification and was published at ISITIA 2023.
IEEE Conference Publication · ISITIA 2023
Word Syllabification for Indonesian Language using Transformer
Developed a character-level syllable-tagging approach with a Transformer architecture for Indonesian syllabification. The work used KBBI and named-entity corpora and reported a 3.68% Word Error Rate, improving on the 3.75% result cited as the previous best deep-learning model in the project evaluation.
TransformerDeep LearningNLPIndonesian LanguageSyllabification
04 / Open source
Selected public projects.
Public work cross-checked against the GitHub evidence snapshot and my LinkedIn project history—focused on developer tooling, backend architecture, full-stack frameworks, and practical AI.
AI context · Database tooling
db2toon
A Go CLI that turns existing database schemas into compact, human-readable TOON context for developers and AI coding agents. It supports MCP and multiple database engines, helping reduce schema-context overhead compared with raw SQL or verbose interchange formats.
PostgreSQLMySQL / MariaDBSQLiteDuckDBCockroachDB
Go · Full-stack architecture
Clean Fullstack Go + Vite + React
A production-oriented full-stack boilerplate that embeds a Vite + React frontend into a Go binary while keeping frontend and backend boundaries explicit. Designed to ship as one binary early, then detach into API + CDN deployment later without rewriting the product architecture.
GoReactViteTailwind CSSClean Architecture
Architecture · Modular monolith
Go PSTE Modular Monolith
An open-source Go architecture built around Plug, Swap, Toggle, Extract: swap infrastructure implementations without touching business logic, toggle features through configuration, and keep domain modules extractable when microservices are actually justified.
GoEcho / Gin / FiberPostgreSQL / MongoDBRabbitMQ / RedpandaS3 / GCS
TypeScript · Full-stack framework
bev-fs
A Bun + Elysia + Vue full-stack framework built around deployment freedom and end-to-end TypeScript safety, with directory-based API/page routing, automatic route discovery, middleware composition, scaffolding templates, and single-port production deployment.
BunElysiaVue 3TypeScriptTailwind optional
Accessibility · Vision-language AI
MacaUang · Camera Money Detector
A Flutter mobile app that combines the device camera, Claude 3.5 Haiku vision-language capabilities, and text-to-speech to identify banknotes and announce denominations—designed to support visually impaired users.
FlutterDartClaude VLMText-to-SpeechMobile
Next.js · ERP-ready monolith
NextJS Fullstack Monolith
An MVP-oriented monolith for small teams and solo engineers with explicit server/client/shared boundaries, a Handler → Service → Repository backend, service-owned transactions, shared API contracts and RBAC, JWT auth, and S3-compatible file uploads.
Next.jsReact 19PostgreSQLTailwind CSS v4shadcn/uiRBAC
Applied AI · Developer library
Natural language → query
A Go library for translating plain-language requests into SQL or NoSQL queries using embeddings and LLM-assisted generation—part of a broader focus on LLM APIs, structured context, and AI-powered developer tooling.
SQL / NoSQLEmbeddingsLLM-powered tooling
NLP · Social automation
JKT48 NLP Bot
A Python/Tweepy social-media analysis bot that automated NLP tasks around public JKT48 content, including sentiment analysis, emotion analysis, and word-cloud generation.
PythonTweepyNLPSentiment AnalysisEmotion Analysis
More public experiments include PostgreSQL tooling, KNN-from-scratch work in Go, Flutter prototypes, and a Telegram-to-Discord live notification bridge. The GitHub profile has the full public history.
03 / Production scope
Private work, summarized responsibly.
The evidence includes significant private-repository activity. The details below intentionally describe engineering scope and technology patterns only—without repository names, links, internal product names, or commit-level details.
Production APIs & worker systems
High-activity Go codebases covering API services, background workers, PostgreSQL-backed workflows, service integration, build automation, and containerized deployment.
GoPostgreSQLDockerMakeShell
Operational dashboards & product interfaces
Full-stack web applications, ERP-oriented workflows, and internal dashboards focused on operations, reporting, configurable product behavior, and production-grade user interfaces.
TypeScriptNext.jsTanStack StartERPMetabaseDocker
Platform services & integrations
Infrastructure-adjacent work including messaging gateways, shared service contracts, feature-control tooling, automation, and systems designed to support multiple internal applications.
GoTypeScriptProtobufAutomation
AI/ML, document intelligence & assisted workflows
Applied ML and LLM-powered systems spanning model APIs, agentic workflows, document understanding, transformer-based models, classical gradient boosting, and cloud-hosted experimentation.
AWS SageMakerXGBoostTensorFlowTransformersDeep LearningDonut VLMLangGraphpandasNumPy
06 / Stack signal
Technology usage across repositories.
Repository counts from the evidence snapshot are a signal of repeated exposure, not a claim that every repository has equal depth or production importance. Additional technologies supplied as experience are listed separately below without invented repository counts.
Go
44 repos
Shell
30 repos
CSS
28 repos
HTML
27 repos
Dockerfile
27 repos
JavaScript
26 repos
TypeScript
23 repos
Makefile
17 repos
Python
11 repos
AI / ML
Modeling & deep learning
Experience across classical ML, neural architectures, document intelligence, and transformer-based systems.
XGBoostTensorFlowTransformersDeep LearningDonut VLMNLPSentiment AnalysispandasNumPy
LLM systems
LLM-powered products & tools
Building AI features and developer tools around model APIs, retrieval/context patterns, and graph-based agent workflows.
LLM APILangGraphEmbeddingsAI AgentsLLM-powered ProductsMCPClaude VLM
Cloud / ML platform
Managed model workflows
Cloud-oriented machine-learning workflows including model experimentation, training, deployment, feature/data preparation, and supporting data pipelines.
AWS SageMakerPythonpandasNumPyModel ServingData Pipelines
Backend / integrations
Service architecture & external platforms
Production backend and integration work across synchronous APIs, gRPC contracts, event-driven processing, identity, caching, and third-party platform integrations.
GoGingRPCProtobufApache KafkaRedisMariaDBKeycloak / OIDCREST APIsClean ArchitectureTM Forum
Product engineering
Modern web & enterprise systems
Full-stack TypeScript product development spanning modern React meta-frameworks, ERP-style operational systems, analytics dashboards, and business reporting.
TanStack StartNext.jsReactVue 3BunElysiaFlutterDartTypeScriptERPMetabase
07 / Approach
A practical engineering bias.
Small surface area
Prefer understandable systems, explicit dependencies, and operational simplicity over unnecessary framework weight.
Build the tool you need
When a workflow is repetitive or awkward, I tend to turn it into a CLI, generator, gateway, library, or small internal platform.
Cross the boundary
Backend is the center of gravity, but I'm comfortable moving into TypeScript UI work, ERP workflows, cloud ML infrastructure, model integration, and AI product prototyping when the product needs it.
Learn from fundamentals
Public projects range from algorithms and ML experiments to full-stack frameworks and DB tooling—evidence of learning by implementing, testing, and shipping.
Open source profile
Explore the code behind the public work.
For source, experiments, and developer tools, explore GitHub. For professional history and connections, visit LinkedIn; for the complete formal employment and education timeline, use the CV. Based in Bandung, Indonesia.