AI Engineering and Architecture Lead

About PharmaEssentia: It’s not often you get the chance to make a real impact on the lives of others, while expanding your own possibilities. You’ll find that rare opportunity at PharmaEssentia. Join us, and let’s transform lives, together. PharmaEssentia Corporation is a rapidly growing biopharmaceutical innovator. We are leveraging deep expertise and proven scientific principles to deliver effective new biologics for challenging diseases in the areas of hematology and oncology, with one product approved and a diversifying pipeline. We believe in the potential to improve both health and quality of life for patients with limited options today through the combination of rigorous research and innovative thinking. Founded in 2003 by a team of Taiwanese-American executives and renowned scientists from U.S. biotechnology and pharmaceutical companies, today we are listed on the Taiwan Stock Exchange (TWSE: 6446) and are expanding our global presence with operations in the U.S., Japan, Singapore, South Korea, and China, along with a world-class biologics production facility in Taichung. Position Summary The 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 Responsibilities Architecture & 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 Arrangement This 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 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 EEO Statement At PharmaEssentia USA, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants without regard to race, color, religion, sex, pregnancy (including childbirth and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. PharmaEssentia USA believes that diversity and inclusion among our team are critical to our success as a global company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. PharmaEssentia does not accept unsolicited agency resumes. Staffing agencies should not send resumes to our HR team or to any PharmaEssentia employees. PharmaEssentia is not responsible for any fees related to unsolicited resumes from staffing agencies. At PharmaEssentia, our goal is to treat as many people with cancer as possible. That means challenging the status quo with better science that leads to better lives. By joining our team, you will not only expand your own possibilities, but you will contribute to expanding options for people with cancer. #J-18808-Ljbffr PharmaEssentia U.S.A.