Job Description :

We are looking for passionate and driven professionals to join DataZymes, a next-generation analytics and data science company founded in 2016. At DataZymes, we focus on driving technology-led innovation and helping clients maximize the value of their data and analytics investments through cutting-edge platforms and consulting expertise.

This role is a builder-leader position. You will architect and ship multi-agent systems that operate autonomously across pharma data pipelines, regulatory intelligence workflows, and cross-functional analytics use cases. You will write code, own production deployments, and lead a small team doing the same.

Requirements :

- Design and build end-to-end agentic systems combining LLMs, multi-agent orchestration, enterprise data pipelines, and pharma-specific business logic.

- Select and implement the right orchestration approach across no-code, low-code, and pro-code patterns.

- Architect retrieval and knowledge services (RAG, knowledge graphs) over structured and unstructured pharma data.

- Build observability, monitoring, and evaluation frameworks to track agent behavior in production.

- Integrate with upstream pharma data platforms (IQVIA, Symphony, Komodo, Veeva) and downstream delivery surfaces.

Pharma Domain Application :

- Translate commercial analytics, medical affairs, and clinical operations workflows into agentic automation opportunities.

- Build agents that operate over 21 CFR Part 11-aware environments.

- Develop intelligent document processing pipelines for clinical study reports, drug labels, HEOR submissions, and payer dossiers.

Leadership & Client Delivery :

- Lead a team of AI engineers and ML practitioners. Set technical direction, review architecture decisions, and maintain a high bar for production quality.

- Partner with client-facing teams to scope agentic AI engagements.

- Communicate complex agent system behavior to non-technical pharma stakeholders.

- Champion AI governance practices aligned with industry standards.

What You Bring :

Technical Depth :

- 8+ years in software or ML engineering; 3+ years with production LLM or agentic AI systems.

- Hands-on proficiency with agentic frameworks : LangGraph, LangChain, AutoGen, CrewAI, or equivalent.

- Direct SDK experience : Anthropic, OpenAI, Google Vertex AI.

- Python fluency. Ability to build, test, and deploy production code.

- Strong RAG architecture skills : chunking strategies, embedding models, vector stores, knowledge graphs.

- Cloud-native deployment : AWS, Azure, or GCP. Containerization (Docker, Kubernetes), CI/CD, infrastructure-as-code.

Pharma / Life Sciences Domain :

- Working knowledge of pharma commercial data ecosystems : Rx/claims data, NPI-level analytics, market access.

- Familiarity with regulated data environments : GxP, 21 CFR Part 11, HIPAA.

- Exposure to medical affairs analytics, real-world evidence, clinical operations, or HEOR workflows.

Leadership & Communication :

- 5+ years leading technical teams or delivery workstreams.

- Track record of shipping production AI solutions with measurable business impact.

- Comfortable in executive-level conversations.

- Strong written communication skills.

Good To Have :

- Experience with Veeva Vault, Medidata, or IQVIA platform integrations.

- Knowledge of RLHF and fine-tuning workflows.

- Familiarity with EU AI Act and FDA guidance on AI/ML.

- Prior consulting or services-firm experience.