Responsibilities
- Collaborate with cross functional teams (product management, user experience, engineering, field teams) and customers to propose, build and test fast-moving prototypes that bring AI ideas to life in Precisely products and create value for our customers
- Leverage AI agents, generative AI, and traditional machine learning models to balance functional accuracy, speed, and cost in the prototypes
- Evaluate new AI technologies, tools, models, and platforms such as AWS Bedrock, Azure OpenAI, Hugging Face, vector DBs and make recommendations for specific use cases
- Track industry trends and research to guide innovation and experimentation, present it to internal teams and as part of ongoing Technology Knowledge sharing forum
- Develop good understanding of competitive landscape in data management industry to drive AI/ML innovation in Precisely products
- Provide technical leadership to engineering teams
- Work in a fast-paced, agile team that embraces change and continuous learning
Requirements
- MS degree or higher in Computer Science, Data Science or a related field
- 5+ years of professional software development experience, including 2+ years focused on applied AI/ML
- Hands-on experience with LLMs, vector databases, RAG pipelines, AI agent frameworks
- Experience with model evaluation methodologies, and benchmarking tools
- Experience with cloud ML platforms, services and typical coding languages, such as AWS Bedrock, ML Flow, SageMaker, Azure ML, Python, SQL
- Understanding of data science principles and basic statistical evaluation methods
- Excellent communication skills and a collaborative mindset
- Curiosity and drive to stay ahead in the fast-moving AI space
- Experience with agentic AI frameworks and orchestration, e.g. Pydantic or crew.ai
- Experience applying a range of AI/ML techniques and advanced analytics, including predictive modeling, deep learning, and data mining.
- Experience with CI/CD pipelines and DevOps practices using GitHub Actions or similar
- Knowledge of containerization using Docker
- Domain experience in data integration, data quality, location intelligence, data enrichment
