Director, Applied AI Engineering – Life Sciences Markets

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Vi

WebsiteLinkedInAll Job Openings

51 - 200 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Vi is a company that leverages artificial intelligence to help health organizations improve member health outcomes and financial returns. The company provides an AI SaaS platform that offers solutions for efficient acquisition, personalized engagement, and predictive retention throughout the member lifecycle. Vi focuses on maximizing acquisition, enrollment, engagement, retention, upsells, and health outcomes with superior ROI. Their platform is designed to lower the cost per acquisition, enhance member engagement and retention, and transform operations with their generative AI technology. Vi works with leading global health enterprises to drive results at scale while ensuring privacy and data security standards are met.

📋 Description

• Build and lead technical delivery of AI applications within Vi’s Life Science Markets squad • Design systems, write production code, integrate models, and ship AI workflows • Personally build and ship core AI services and workflows • Own critical implementation work and resolve technical blockers with engineers, data scientists, and domain experts • Lead squad engineers and overall execution • Set implementation standards, review code and architecture, and coordinate technical priorities and dependencies • Identify life sciences market questions where Vi’s data can add value • Prioritize use cases, define success measures, and create a focused roadmap • Design and implement systems combining ML models, LLMs, retrieval, and workflow automation • Make practical choices about model quality, reliability, latency, and cost • Build automated tests, evaluation datasets, and monitoring for AI outputs and application reliability • Maintain rigorous predictive-model validation, including point-in-time backtesting, baseline comparisons, and leakage and coverage-bias checks • Take prototypes into production and own models, APIs, integrations, deployment, observability, and incident resolution • Build reusable capabilities that scale across therapies, companies, and clients • Work directly with clients and domain experts to understand analytical workflows, explain findings, challenge assumptions, and turn feedback into product priorities

🎯 Requirements

• Strong record of personally building and shipping production AI applications, with technical ownership of complex systems and measurable business outcomes • Experience leading technical delivery across functions while remaining a primary contributor to design, modeling, coding, debugging, and deployment • Deep practical experience integrating ML models and LLMs into production systems, including retrieval, tool use, structured outputs, and evaluation • Ability to assess model limitations and choose methods suited to the available data • Ability to run working sessions with clients' technical and non-technical stakeholders and identify impactful solutions • Ability to translate complex analysis into clear conclusions for senior stakeholders and clients, including limitations of the evidence • Hands-on experience with scalable data pipelines, automated testing, CI/CD, and cloud infrastructure, ideally AWS • Comfortable owning application code and AI deployment • Experience turning bespoke analyses or pilots into products used repeatedly by multiple clients or teams • Background in life sciences, pharmaceutical analytics, or capital markets helpful but not required

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume