Design, develop, and deploy AI/ML solutions, including LLMs, NLP, computer vision, and predictive analytics
Build and implement Retrieval-Augmented Generation (RAG) pipelines and AI-powered applications
Integrate AI solutions into existing enterprise systems and workflows
Design and implement scalable data pipelines for ingestion, transformation, and processing of structured and unstructured data
Develop and maintain data lakehouse architectures
Build ETL/ELT workflows using tools such as Azure Data Factory, Apache Airflow, or similar
Develop end-to-end applications, including frontend, backend, and APIs
Create intuitive user interfaces for AI-driven applications
Deploy applications using cloud-native architectures (AWS, Azure, GCP)
Translate business requirements into technical architectures and working solutions
Integrate AI and data solutions into enterprise and cloud environments
Collaborate with cross-functional teams to deliver production-ready solutions
Clearly articulate complex technical concepts through written documentation, proposals, and solution artifacts

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
4+ years of experience in AI/ML, data engineering, or full-stack development
Strong programming skills in Python, JavaScript/TypeScript, or Java
Experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, OpenAI APIs)
Experience building data pipelines and working with big data technologies
Hands-on experience with cloud platforms (AWS, Azure, or GCP)
Experience with REST APIs, microservices, and frontend frameworks (React, Angular, or Vue)
Experience with LLMs, RAG architectures, and generative AI applications
Familiarity with Databricks, Snowflake, or lakehouse architectures
Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines)

AI/ML Engineer – Data, Full-Stack Solutions

Key skills