Gen AI

The AI Engineer will design, develop, and implement AI models and systems, focusing on turning data into actionable insights through advanced machine learning (ML) and AI techniques. This role involves working with both structured and unstructured data, collaborating with cross-functional teams, and deploying AI solutions in real-world applications.
Key responsibilities include hands-on development of generative AI applications and machine learning models such as classification, regression, clustering, and natural language processing (NLP) to generate actionable insights. The AI Engineer will collaborate with cross-functional teams to ensure that AI solutions align with business needs. Working in an agile development environment, the engineer will contribute directly to production-ready AI applications. Staying up-to-date with advancements in AI and integrating relevant innovations into ongoing projects will be essential. The role also involves continuously monitoring and optimizing AI models to improve accuracy, scalability, reliability, and maintainability. Documenting processes, models, and key learnings is expected, along with contributing to the development of internal AI capabilities. The engineer must also ensure that AI models adhere to ethical standards, privacy regulations, and fairness guidelines.
Qualifications for this role include a bachelors degree in operations research, mathematics, computer science, or a related quantitative field. Candidates should have advanced expertise in Python and familiarity with database systems such as SQL, NoSQL, and Graph databases. Proficiency with generative AI tools, particularly AWS Bedrock, is required, as is a comprehensive understanding of agentic systems and workflows. The ideal candidate will have experience productionizing GenAI services and working with complex datasets. Advanced experience in developing APIs using Python (e.g., with FastAPI) and deploying them to production is expected. Familiarity with CI/CD pipelines, a strong foundation in software development, and a deep understanding of algorithms, optimization, and scaling are also required. Excellent communication and business analysis skills are critical to success in this role.
While not mandatory, experience with cloud engineering, particularly using AWS cloud services, is considered a valuable asset.