Senior Engineer, AI Applications
About The Position
The Senior Engineer, AI Applications is the hands-on builder of PharmaEssentia’s first production AI applications and agents. Reporting to the AI Engineering & Architecture Lead within Global Data & AI Enablement (GDAI), this engineer writes the code that converts governed data assets into tools commercial teams use every day. The first use cases are concrete: patient and HCP opportunity identification, and proactive field alerts that surface meaningful signals instead of asking the field to search dashboards. Backend ETL is delivered by an external vendor into Snowflake, so this role builds on vendor-delivered and internally modeled data rather than owning ingestion. The patterns this engineer establishes — retrieval, orchestration, evaluation, monitoring — become the foundation the rest of the team builds on.
Requirements
- Bachelor’s degree required; technical degree (computer science, engineering, or related field) preferred
- 5+ years building production software, including recent hands-on delivery of LLM-based or agentic applications that real users depend on
- Strong Python and SQL; comfortable working directly against a cloud data warehouse, ideally Snowflake
- Practical experience with retrieval, context management, tool and API integration, and agent orchestration frameworks
- Has built evaluation and monitoring for an AI system, and can explain how quality was measured rather than asserted
- Experience deploying and operating services in a cloud environment, including observability and incident response
Nice To Haves
- Experience in pharmaceutical, biotech, or healthcare commercial data, or another regulated industry
- Integration experience with CRM and field-facing systems (Veeva, Salesforce)
- Enough front-end capability to ship a usable interface without waiting for a dedicated front-end hire
- Experience as an early engineer on a small team, where scope is set by what the business needs rather than by a backlog handed down
Responsibilities
- Build agentic and LLM-based applications against our Snowflake data assets, from first working version through production operation
- Implement retrieval, orchestration, evaluation, and monitoring so that application behaviour is measurable and regressions are caught before users see them
- Deliver early high-value use cases, starting with opportunity identification and proactive field alerts, and iterate on them with real users
- Integrate AI services with the systems the field already uses, so output arrives in workflow rather than in a separate tool
- Establish reusable engineering patterns — prompt and agent structure, evaluation harnesses, deployment, observability — that the team can build on
- Write the documentation, tests, and deployment processes that let a second engineer work on the same codebase without archaeology
- Apply the standards set by the AI Engineering & Architecture Lead for security, cost, and responsible deployment, including how AI output reaching field-facing use is reviewed and logged
- Work with Data Product Engineering to specify the data models and semantic assets applications need, and to flag where delivered data is not fit for purpose
- Work with AI Product Strategy & Value to turn prioritized business problems into shippable scope, and with AI Enablement & Adoption on rollout and user feedback
- Say plainly when a use case will not work as specified, and propose what would
Benefits
- Comprehensive medical coverage
- Dental and vision coverage
- Generous paid time-off
- 401(k) retirement plan with competitive company match
- Medical & Dependent Care Flexible Spending Account
- Up to $150 monthly cell phone reimbursement
- Employee Assistance Program
- Free parking
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
