Key Responsibilities

• Design, build, and deploy scalable, production-ready AI applications, bridging solid software engineering with advanced machine learning, often focusing on LLMs, RAG, and MLOps.
• Mentor junior engineers and lead architecture for complex systems from data to deployment.
• Develop high-quality code that aligns with business objectives, quality standards, and secure development practices.
• Collaborate with a global AI engineering team to understand and analyze business requirements.
• Execute assigned tasks diligently, ensuring consistent progress.
• Work closely with business and technical teams to identify improvements and prioritize user stories.
• Provide regular progress updates during daily standup meetings.
• Adapt to shifting priorities while maintaining project timelines and momentum.

Qualifications

Essential Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Applied Mathematics, Statistics, or related fields.
• 8+ years of experience in software development and machine learning, with expertise in writing and reviewing production-grade Python code and at least 3+ years in AI engineering.
• Strong knowledge of ML frameworks and libraries (e.g., TensorFlow, PyTorch), with hands-on experience implementing ML algorithms at scale.
• Extensive hands-on experience in building and integrating large language models (LLMs) to significantly enhance the capabilities and effectiveness of AI systems.
• Demonstrated expertise in designing and operating distributed, high-throughput, and low-latency system architectures.
• Proficiency in software development using containerization technologies (e.g., Kubernetes, Docker) and frameworks/tools such as FastAPI and Uvicorn.