AI Engineer
We are seeking an AI Engineer who thrives at the intersection of advanced machine learning and reliable software engineering. This role focuses on building GenAI applications that deliver real business value, ensuring models perform accurately, and maintaining high standards of code and system quality.

QUALIFICATIONS

• Minimum 3 years of experience in data engineering or equivalent
• Minimum 3 years of experience in machine learning engineering or equivalent
• Minimum 3 years of software engineering experience
• Hands-on knowledge of frameworks such as LangChain, A2A, MCP, or other GenAI development stacks
• Understanding of LLMs, Generative AI, and Agentic AI
• Experience building and supporting MLOps or DevOps systems
• Familiarity with continuous training, monitoring, and improvement in ML/AI systems
• Cloud certifications in GCP, AWS, or Azure are preferred

What We Offer

• The opportunity to work on forward-looking AI systems with real-world impact
• A collaborative team that values innovation and engineering excellence
• Autonomy to lead initiatives and influence technical direction
• Competitive compensation and professional growth opportunities

Job Type: Fixed term contract
Contract length: 6 months
Pay: $45.00-$90.00 per hour
Expected hours: 35 per week
Work Location: In perso

• Work closely with product managers and developers to design and implement AI-driven solutions that align with business and technical requirements
• Build GenAI applications that integrate non-deterministic LLMs with deterministic software engineering principles
• Develop evaluation frameworks to measure model accuracy, reliability, and fairness
• Deliver regular performance reports and drive improvements based on results
• Write clean, maintainable, and scalable code across the AI pipeline
• Debug, fix, and optimize GenAI applications using prompt engineering, reinforcement learning, and software engineering techniques
• Implement and support MLOps practices for deployment, monitoring, and iteration of models in production
• Ensure compliance with data privacy and security policies when handling training and test data