Position SummaryThe AI Engineering & Architecture Lead owns PharmaEssentia's AI architecture and leads the engineering team that builds on it. This is the most important single hire in the Global Data & AI Enablement (GDAI) plan: the team today has no dedicated AI engineering capability, and this role creates it.
Reporting to the Head of Global Data & AI Enablement, this leader is accountable for turning governed data assets into production AI applications and agents that change how commercial teams work - opportunity identification, proactive field alerts, HCP intelligence, field copilots, next-best-action workflows, and omnichannel intelligence. Backend ETL is delivered by an external vendor into Snowflake, so this role's value sits above that layer: architecture, build-versus-buy judgment, engineering standards, and delivery. Success is measured by sustained adoption and business outcomes, not by the number of tools launched.
Key ResponsibilitiesArchitecture & Build-versus-Buy- Define the AI and application architecture - retrieval, orchestration, agent frameworks, evaluation, observability, and integration patterns - across the GDAI portfolio
- Make and defend build-versus-buy decisions, retaining enough internal capability to own the architecture rather than depending on vendors for judgment or prioritization
- Design for the data environment as it is: vendor-delivered raw data in Snowflake, a semantic layer built under internal oversight, and a roadmap to internalize both over time
Delivery of Production AI Applications- Lead delivery of production AI applications and agents against the Commercial roadmap, from first use case through sustained operation
- Prioritize engineering capacity with AI Product Strategy & Value so that every major initiative has an owner, a business case, and a measured outcome
- Replace dashboard search with proactive delivery: systems that detect meaningful signals and push the right insight to the right person at the right time
Engineering Standards & Responsible Deployment- Set standards for evaluation, testing, monitoring, cost control, security, and responsible deployment, and enforce them across internal and outsourced work
- Establish how AI output destined for field-facing use is reviewed, logged, and kept within promotional, privacy, and medical-commercial separation requirements
Vendors & Team- Evaluate and integrate vendor platforms, and hold vendors to technical account against architecture, security, and quality standards
- Build and mentor the AI engineering team - one senior engineer in the first wave, a second engineer subject to demonstrated adoption and value
Required Qualifications- Bachelor's degree required; technical degree (computer science, engineering, or related field) preferred
- 10+ years in software or ML engineering, including 3+ years leading engineers
- Has shipped and operated LLM-based or agentic applications in production - not prototypes, proofs of concept, or pilots - and can describe what broke and what it cost
- Hands-on ownership of retrieval, orchestration, evaluation harnesses, monitoring, and cost control for AI systems in production
- Experience architecting applications on a cloud data platform, ideally Snowflake
- Demonstrated build-versus-buy decisions, and experience holding a technology vendor to technical account on scope and quality
- Still technical: able to review code, debug a production system, and set standards by example
Preferred Qualifications- Experience in pharmaceutical, biotech, or healthcare commercial environments, or another regulated industry with review and audit requirements
- Experience standing up an AI engineering function from zero rather than inheriting one
- Integration experience with CRM and field-facing systems (Veeva, Salesforce) and marketing platforms
- Familiarity with evaluation, guardrail, and observability tooling for LLM applications
- Experience in an organization where adoption, not delivery volume, was the measure of success
Location and Work ArrangementThis position is based in Burlington, Massachusetts, and follows a hybrid work model requiring on-site presence three days per week.
The expected base salary range for this position is $190,000-245,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education and geographical location. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible for short-term and long-term incentives.
Benefits of working with our team:PharmaEssentia USA strives every day to improve the lives of patients as well as our employees. As a valued member of PharmaEssentia USA, you will enjoy the following 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
