AI Engineer

🚀 About SimuPhish

SimuPhish is an AI-driven Human Risk Management and Phishing Simulation platform built to help organizations strengthen their human firewall through realistic simulations, gamified awareness, and data-driven insights. We empower employees to become the strongest defense against cyber threats.

💡 Role Overview

We are looking for a hands-on AI Engineer with 2 to 6 years of experience to design, build, deploy, and scale AI-powered solutions. This role requires strong foundations in machine learning, modern AI (including GenAI), and solid software engineering practices to deliver production-ready AI systems.

🧩 Key Responsibilities

• Design, develop, and integrate AI/ML and Generative AI models into production systems.
• Build and optimize ML pipelines covering data preparation, training, evaluation, and inference.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and advanced prompt engineering techniques.
• Develop and deploy scalable AI services using microservices architecture.
• Deploy AI solutions on cloud environments using containerization and CI/CD pipelines.
• Set up monitoring, logging, and performance tracking for deployed AI models.
• Build and integrate AI capabilities through APIs and system-level integrations.
• Develop and experiment with AI agents capable of multi-step reasoning, tool usage, and autonomous workflows.
• Collaborate with cross-functional teams to translate business problems into AI-driven solutions.
• Ensure code quality, security, scalability, and maintainability through best software engineering practices.

Essential Skills & Technical Expertise

1. Programming Proficiency

• Strong proficiency in Python for developing, training, and integrating AI/ML and GenAI models.

2. Machine Learning & Modern AI

• Solid understanding of core ML algorithms and deep learning concepts.
• Practical experience with modern architectures, especially Transformers.
• Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.

3. Vector Databases, RAG & Prompt Engineering

• Experience working with vector databases for semantic search and retrieval.
• Ability to design and implement RAG pipelines.
• Advanced prompt engineering skills to optimize LLM outputs.

4. Deployment, MLOps & AI Integration

• Experience deploying AI models in cloud environments.
• Hands-on knowledge of Docker, Kubernetes, and CI/CD pipelines.
• Understanding of MLOps practices including model versioning, monitoring, and retraining.
• Experience with API-based AI integration and AI calling mechanisms.

5. Data Management

• Experience handling large datasets including data cleaning and feature engineering.
• Working knowledge of SQL, NoSQL, and vector databases.
• Familiarity with big data tools and data pipelines is a plus.

6. Microservices

• Experience designing and deploying AI-driven microservices.
• Understanding of service-to-service communication and scalability concerns.

7. AI Agents & Generative AI

• Hands-on experience building AI agents using LLMs.
• Understanding of multi-step reasoning, tool usage, and autonomous AI workflows.
• Exposure to other Generative AI models such as image or video generation is a plus.

8. Software Engineering & System Design

• Strong grasp of software engineering best practices including testing, version control, and documentation.
• Ability to design robust, scalable, and secure AI systems.

✅ Qualifications

·       Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

·       2 to 6 years of relevant hands-on experience in AI/ML engineering roles.

🌟 Why Join Us

• Work with a global cybersecurity brand making a real impact.
• Hybrid flexibility with a collaborative and innovative team culture.
• Opportunity to experiment, innovate, and grow with creative freedom.
• Inclusive, supportive environment that values ideas and individuality.