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.