Director, Applied AI Engineering – Life Sciences Markets

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the technical delivery of AI applications within Vi’s Life Science Markets team.

• Design systems, develop production code, integrate models, and deploy AI workflows.

• Personally create and deploy core AI services and workflows.

• Take ownership of essential implementation tasks and address technical challenges alongside engineers, data scientists, and subject matter experts.

• Guide the squad engineers and oversee overall project execution.

• Establish implementation standards, review code and architecture, and manage technical priorities and dependencies.

• Identify key questions in the life sciences market where Vi’s data can provide significant value.

• Prioritize use cases, define success criteria, and develop a focused roadmap.

• Design and implement systems that integrate ML models, LLMs, retrieval, and workflow automation.

• Make informed decisions regarding model quality, reliability, latency, and cost considerations.

• Develop automated tests, evaluation datasets, and monitoring systems to ensure AI output and application reliability.

• Maintain strict validation of predictive models, including point-in-time backtesting, baseline comparisons, and checks for leakage and coverage bias.

• Transition prototypes into production, taking ownership of models, APIs, integrations, deployment, observability, and incident resolution.

• Create reusable capabilities that can scale across various therapies, companies, and clients.

• Collaborate directly with clients and domain experts to understand analytical workflows, articulate findings, challenge assumptions, and convert feedback into product priorities.

⛳️ Requirements

• Proven track record of independently developing and deploying production AI applications, with technical ownership of complex systems and measurable business outcomes.

• Experience leading technical delivery across multiple functions while also actively contributing to design, modeling, coding, debugging, and deployment.

• Extensive practical experience in integrating ML models and LLMs into production systems, including retrieval, tool usage, structured outputs, and evaluation processes.

• Ability to evaluate model limitations and select methods appropriate for the available data.

• Capability to facilitate working sessions with both technical and non-technical stakeholders and pinpoint impactful solutions.

• Skill in translating complex analyses into concise conclusions for senior stakeholders and clients, including recognizing the limitations of the evidence presented.

• Hands-on experience with scalable data pipelines, automated testing, CI/CD, and cloud infrastructure, preferably AWS.

• Comfortable with taking ownership of application code and AI deployment.

• Experience in transforming custom analyses or pilot projects into products that are utilized repeatedly by various clients or teams.

• A background in life sciences, pharmaceutical analytics, or capital markets is advantageous but not mandatory.

🏝️ Benefits

• Opportunity to work on innovative AI projects in the life sciences sector.

• Collaborative and dynamic work environment.

• Access to professional development and training resources.

• Competitive salary and comprehensive benefits package.