GenAI Engineer

Join our dynamic team at the forefront of cybersecurity innovation, where cutting-edge generative AI meets real-world challenges. As a GenAI Engineer, you’ll work closely with our Lead AI Engineer, R&D and product teams to drive data-centric projects that leverage Large Language Models (LLMs) and intelligent agent systems. You will play a pivotal role in designing, developing, and deploying production-level AI solutions—from initial data collection and model optimization to sophisticated cloud-based deployment and monitoring.

At our innovative startup, we cultivate a collaborative and team-centric environment that values creativity, technical excellence, and continuous learning. We empower our team members to explore new ideas, drive impactful projects from day one.

Generative AI Development & Model Optimization:

• LLM Production Solutions: Develop sophisticated LLM-based production-level solutions.
• Model Evaluation & Tuning: Evaluate, select, and fine-tune models to meet specific performance and security requirements.
• AI Systems & Agent development: Design, build, and deploy systems, agents, and workflows that enable complex decision-making processes—utilizing modern frameworks (e.g., LangChain, LangGraph) to manage and coordinate multiple AI agents.
• RAG Pipeline Enhancement: Build and optimize Retrieval-Augmented Generation (RAG) pipelines to boost accuracy.
• Data Engineering & Analysis: Execute data scraping, optimization, and analysis to support robust AI solution

Cloud Infrastructure & Deployment:

• AWS Service Utilization: Leverage AWS services (ECS, Lambda, S3, Bedrock, SageMaker) to deploy scalable and secure AI solutions.
• Cloud Architecture: Architect cost-effective, secure cloud infrastructures for high-performance AI workloads.

• Proficiency in Python and modern software engineering practices.
• Hands-on experience with LLMs, prompt engineering, fine-tuning methodologies, agent development, and RAG implementation.
• Strong working knowledge of AWS services (S3, Bedrock, Lambda) and cloud architecture.
• Proficiency with Git and collaborative development workflows.

• Familiarity with cybersecurity principles and best practices.

• Experience: 2+ years of experience in data science, AI development, or a related field.
• Education: Bachelor’s or Master’s degree in a quantitative discipline or a closely related field.

We recognize that not every candidate will meet every qualification listed above. If you’re passionate about AI innovation and believe your skills align with our vision, we encourage you to apply.