Generative AI Delivery Lead, Associate Director - Life Sciences
- Lead the delivery of generative AI projects from inception to production, ensuring all project goals are met on-time, on-budget, and to the highest standard.
- Work closely with clients to understand their requirements and objectives and translate these into actionable project plans and roadmaps.
- Collaborate with project managers, solution architects, engineers, and data scientists to ensure project tasks are being executed and delivered on time and within budget.
- Review and provide feedback on project deliverables to ensure quality and accuracy.
- Identify and mitigate project risks, and escalate issues as needed to ensure project success.
- Communicate effectively with stakeholders at all levels of the organization to ensure project progress is understood and milestones are achieved.
- Provide technical pre-sales support, including participating in client meetings, preparing technical proposals, and presenting solutions to clients.
- Stay up-to-date with the latest generative AI technologies, trends, and best practices.
- Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field.
- Experience leading the delivery of both generative & traditional AI projects across the end to end SDLC process.
- Proven experience in leading development teams across different geographical locations using offshore or nearshore delivery models.
- Proficiency in project management methodologies, including Agile, Scrum, and Waterfall.
- Strong leadership and communication skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
- Excellent problem-solving, critical thinking, and analytical skills.
- Proficiency in object orientated programming languages such as Python, Java, or Scala.
- Knowledge of generative AI architectural patterns including RAG & fine tuning.
- Experience training & deploying machine learning models using a range of techniques (e.g. Classification, Regression, Neural Networks, etc).
- Experience with developing and deploying applications in cloud environments, such as AWS, Azure, or Google Cloud Platform.
- Understanding of how to design and implement RESTful APIs for generative AI applications.
- Familiarity with web development technologies, such as HTML, CSS, JavaScript, and React.
- Proficiency in database management systems and SQL.
- Experience developing ETL pipelines using distributed computing and parallel processing frameworks, such as Spark.
- Knowledge of Data Architecture & Data Modelling techniques.
- Experience working with modern data & AI platforms such as Databricks, Dataiku, DataRobot, etc.
- Knowledge of containerization platforms such as Docker and Kubernetes.
- Familiarity with software development tools, such as JIRA, Confluence, and Git.
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