AI Engineer Senior Associate | Hybrid

As an AI Engineer Senior Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Advisory practice, you will focus on leveraging advanced analytics and statistical techniques to extract insights from large datasets and drive data-driven decision-making. You will work on exploratory and descriptive analysis, statistical modeling, and creating data visualizations to help solve complex business problems and inform strategic decisions.

As a Senior Associate, you will build meaningful client connections and learn how to manage and inspire others. Navigating increasingly complex situations, you will grow your personal brand and deepen your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality solutions. Embracing increased ambiguity, you will be comfortable when the path forward isn’t clear, using these moments as opportunities to grow.

• →Developing and implementing advanced data solutions to transform raw data into actionable insights
• →Leveraging statistical modeling and data visualization techniques to solve complex business problems
• →Utilizing machine learning algorithms and tools such as TensorFlow and Scikit-Learn to enhance data-driven decision-making
• →Conducting exploratory and descriptive analysis to inform strategic decisions and drive business growth
• →Building and maintaining data pipelines and data lakes to support large-scale data processing
• →Collaborating with clients to understand their data needs and deliver tailored analytics solutions
• →Applying programming skills in languages such as C++ and R to develop and optimize data science workflows
• →Confirming data quality and integrity through rigorous data engineering practices
• →Mentoring junior team members in data science methodologies and techniques
• →Engaging in continuous learning to stay updated with the latest advancements in artificial intelligence and data science

• At least a Bachelor's degree
• At least 4 to 7 years of experience
• Oral and written proficiency in English required
• Strong full-stack or backend development skills, including Python, Angular or React, RESTful APIs, microservices, SQL/NoSQL databases, testing, and software architecture.
• Hands-on experience building AI-integrated applications, using LLMs, RAG, embeddings, vector databases, and frameworks such as LangChain, LlamaIndex, or Autogen.
• Proven cloud and DevOps capability, including Azure, AWS, or GCP deployment, Docker, Kubernetes, CI/CD, Git, security, reliability, and scalability.

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating proficiency in data science algorithms and workflows
• Utilizing machine learning and deep learning techniques effectively
• Excelling in complex data analysis and predictive modeling
• Applying knowledge of programming languages such as C++, R, and MATLAB
• Leveraging experience with data engineering and data pipeline management
• Navigating ambiguity while building meaningful client relationships