# Skills | Anis Messas — Engineering Capabilities

Technical skills across programming languages, application development, data, DevOps, architecture, messaging, performance, security, software engineering, and applied AI.

## Programming languages

- **JAVA:** DISTRIBUTED SYSTEMS, MICROSERVICES, EVENT-DRIVEN ARCHITECTURE
- **TYPESCRIPT:** FRONTEND, BACKEND, FULL STACK
- **PYTHON:** PROTOTYPING, AUTOMATION, AI / COMPUTER VISION

## Data layer

- POSTGRESQL
- MYSQL
- MSSQL
- MONGODB
- NEO4J

## Application development

### FRONTEND

Component-driven web applications, responsive interfaces, and modern TypeScript tooling.

- **REACT:** TypeScript · Vite
- **ANGULAR:** TypeScript · SPA

**FOUNDATION & STYLING**

- HTML
- CSS
- SASS
- TAILWIND
- BOOTSTRAP
- VITE

### BACKEND — JAVA / SPRING

Java application services, persistence layers, and APIs built around Spring.

- **SPRING BOOT:** Java · REST
- **HIBERNATE / JPA:** Persistence · Data

**FRAMEWORKS & APIs**

- SPRING FRAMEWORK
- REST API
- GRAPHQL

### BACKEND — TYPESCRIPT / NODE.JS

TypeScript backend services, APIs, and serverless workloads across Node.js and cloud functions.

- **NODE.JS:** TypeScript · Services
- **SERVERLESS:** Azure Functions · AWS Lambda

**SERVERLESS & APIs**

- AZURE FUNCTIONS
- AWS LAMBDA
- REST API
- GRAPHQL

### BACKEND — PYTHON

Python services, automation, and prototyping used across application workflows and integrations.

- **PYTHON SERVICES:** APIs · Automation
- **PROTOTYPING:** Integration · Tooling

**FRAMEWORKS & APIs**

- DJANGO
- FAST API

## DevOps

### CI / CD

Build, test, and delivery automation across different project environments.

- **Technologies:** GITHUB ACTIONS, AZURE PIPELINES, JENKINS

### CONTAINERS

Repeatable application packaging from local development to deployment targets.

- **Technologies:** DOCKER

### ORCHESTRATION

Container deployment, configuration, and lifecycle management.

- **Technologies:** KUBERNETES, HELM

### CLOUD

Cloud environments used for application hosting, infrastructure, and delivery.

- **Technologies:** AWS, AZURE, GOOGLE CLOUD, ORACLE CLOUD

### Foundations

- **INFRASTRUCTURE AS CODE:** TERRAFORM, PULUMI, BICEP
- **OPERATING ENVIRONMENT:** LINUX

## Architecture

### MICROSERVICES

Service boundaries, independent responsibilities, and distributed application flows.

### EVENT-DRIVEN

Asynchronous communication and event-based coordination between components.

### TRANSACTIONAL SYSTEMS

Consistency, state transitions, and safe concurrent updates.

## Messaging

- KAFKA
- RABBITMQ

## Performance

- MULTITHREADING
- CACHING
- RATE LIMITING
- HIGH AVAILABILITY
- LOAD BALANCING
- PERFORMANCE OPTIMIZATION

## Security

### IDENTITY

Standards and flows used to establish user or service identity.

- **Technologies:** OAUTH2, OPENID CONNECT

### TOKEN

Token-based transport of identity, claims, and authorization context.

- **Technologies:** JWT

### AUTHORIZATION

Role and permission checks that decide what an authenticated identity can access.

- **Technologies:** RBAC

### APPLICATION PROTECTION

Traffic controls that protect services and help preserve availability under load.

- **Technologies:** RATE LIMITING

## Engineering disciplines

### COMPUTER SCIENCE

Core problem-solving foundations used across application and systems work.

- ALGORITHMS
- DATA STRUCTURES
- COMPETITIVE PROGRAMMING

### PROBLEM SOLVING

Turning complex constraints into efficient and maintainable solutions.

- ALGORITHM DESIGN
- OPTIMIZATION
- PROBLEM DECOMPOSITION

### SOFTWARE DESIGN

Structuring code around clear responsibilities, reusable abstractions, and maintainable behavior.

- OOP
- DESIGN PATTERNS

### TESTING

Verification practices used to keep changes predictable and protect system behavior.

- TDD
- UNIT TESTING
- INTEGRATION TESTING

## AI workflow

### COMPUTER VISION

Image processing and visual analysis used to extract structure, features, and useful signals from visual data.

- **Technologies:** OPENCV

### MODELS & LEARNING

Neural-network concepts and model workflows used when working with learned representations and AI systems.

- **Technologies:** NEURAL NETWORKS

### AI PLATFORMS

Managed AI services and provider APIs used to bring model capabilities into production applications.

- **Technologies:** OPENAI API, AZURE OPENAI, VERTEX AI, AWS BEDROCK

### APPLICATION TOOLING

Application-layer tooling used to connect model capabilities with workflows, context, and surrounding software.

- **Technologies:** LANGCHAIN