Responsibilities

• Apply your knowledge of AI systems and software engineering to develop solutions that solve real business problems.
  

• Collaborate closely with Data Science and Data Engineering professionals to address technical challenges and ensure the use of best practices in Data & AI.
  

• Contribute to the development and optimization of applied AI components, focusing on performance and scalability.
  

• Work with generative AI models, including LLMs, to design prompts and solutions tailored to specific use cases.
  

• Help implement AI solutions while following industry best practices for moderation, security, monitoring, and compliance.
  

• Apply principles of Responsible AI across all stages of the solution lifecycle.
  

• Support the design and measurement of model outputs, assisting in the development of standard and custom evaluation metrics to align with business objectives.
  

• Help translate AI research and proof-of-concepts (PoCs) into production-ready features that integrate into larger systems.
  

• Assist in selecting and applying appropriate evaluation metrics to ensure robustness and fairness in AI solutions.
  

• Analyze unstructured data (such as text, audio, and images) to extract patterns and generate actionable insights that align with business objectives.
  

  
  
  
  

• Hands-on experience in applied AI, with a strong foundation in machine learning, NLP, LLMs, and statistical analysis.
  

• Understanding of different generative AI models and their trade-offs for various use cases.
  

• Experience with embeddings and vector databases, with the ability to evaluate and apply them for optimized data ingestion and retrieval.
  

• Proven experience in building AI-driven features that integrate with traditional software systems.
  

• Experience developing APIs and working with backend/orchestration platforms.
  

• Proficiency in Python and familiarity with relevant AI/ML libraries and frameworks.
  Ability to craft and refine prompts for different AI applications.

• Knowledge of AI system testing and evaluation using up-to-date methodologies and industry best practices.
  

• Experience working with cloud platforms and AI tools such as AWS Bedrock, Azure AI Services, or Google Vertex AI.
  

• Strong collaboration skills and ability to work effectively with cross-functional teams.
  

• Clear and effective communication skills for both technical and non-technical stakeholders.