Forward Deployed Engineer

We are looking for a Forward Deployment Engineer (FDE) to sit at the intersection of AI engineering and customer success. You will work directly with pharma clients to deploy, integrate, and scale AI-powered solutions, translating complex technical capabilities into real-world workflows. This is a hands-on, client-facing engineering role where you own outcomes, not just deliverables.

Responsibilities:

• Partner with pharma clients from pilot to production, leading technical onboarding, integration, and go-live.
• Build and maintain API integrations between AI platforms and client systems (EHR, CTMS, regulatory, lab, and commercial systems).
• Deploy AI/ML models and inference services on cloud infrastructure (AWS, Azure, or GCP), ensuring reliability, security, and scalability.
• Translate domain-specific pharma workflows (clinical trials, pharmacovigilance, regulatory submissions, drug discovery) into technical requirements.
• Debug integration issues in production, triage model behavior, and coordinate with internal engineering teams on fixes.
• Develop reusable reference architectures, integration playbooks, and technical documentation.
• Act as a trusted technical advisor to client engineering and IT teams.
• Surface product feedback from the field to inform the roadmap.

What Success Looks Like:

• In the first 30 days, you're embedded with a client team and have shipped at least one integration. In 90 days, you're running deployments independently and have become the go-to technical resource for your accounts.

Requirements:

• Skills: Data Engineer, AI Platform, Pharma.

Engineering:

• 4+ years of software or integration engineering experience.
• Strong proficiency in Python; experience with REST API design, OAuth, and webhook integrations.
• Hands-on cloud deployment experience (AWS, Azure, or GCP); containers, serverless, IAM, and networking.
• Familiarity with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering basics.
• Hands-on data engineering experience with Snowflake or Databricks, data pipelines, transformations, and working with large structured/unstructured datasets.
• Experience with CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, or similar).

Domain:

• Working knowledge of the pharmaceutical value chain: clinical development, regulatory affairs (FDA/EMA), pharmacovigilance, or commercial operations.
• Familiarity with pharma data standards (CDISC, HL7/FHIR, MedDRA) is a strong plus.
• Understanding of pharma compliance and data privacy requirements (21 CFR Part 11, GxP, HIPAA).

Soft Skills:

• Comfortable in ambiguous, fast-moving client environments.
• Strong communicator able to explain technical concepts to non-technical stakeholders.
• Self-directed; can manage multiple client engagements simultaneously.

Nice to Have:

• Experience with RAG pipelines, vector databases, or document AI (OCR, NLP).
• Background in a pharma/biotech company or a consulting firm serving the life sciences sector.
• Familiarity with platforms like Veeva, Medidata, or Oracle Health Sciences.