Note: Red Swan Labs is the hiring partner of our client.

About the Employer

Company Type: Service

Company Size: Startup / Small Enterprise

Company Target: B2B

Funding Stage: Bootstrapped The employer empowers the Pharma industry with their creative products.

The idea germinated with the realization that Pharma Commercial teams had few alternatives to the antiquated and inefficient solutions offered by traditional consulting and technology companies. Already a laggard in analytical maturity, the Pharma industry had been facing challenges to adapt to a Big Data world.

They saw that the products offered by technology companies were too rigid and generic to handle novel problems. The custom solutions offered by consulting organizations took too long to deploy and required many services to maintain and improve.

They felt the need for a different approach to finding solutions and they knew it would take a different kind of company to build it.

Roles & Responsibilities

1. Design and implement complex components of agentic pipelines — multi-agent graphs, tool orchestration layers, retrieval modules, and memory systems — using LangGraph, AutoGen, CrewAI, or equivalent
2. Take ownership of full sub-system designs: define agent topology, data flows, API contracts, and failure handling for a bounded scope
3. Build and optimise production RAG pipelines: document ingestion, chunking strategy, embedding selection, hybrid search, retrieval evaluation, and latency tuning
4. Integrate agentic systems with pharma data platforms (IQVIA, Symphony, Komodo,



Veeva) via REST, event-driven hooks, and batch pipeline patterns
5. Own observability for components: instrument trace logging, cost metrics, drift alerts, and evaluation harnesses using LangSmith, Helicone, or equivalent
6. Lead CI/CD for owned modules: containerisation (Docker/Kubernetes), automated test suites, staging gate criteria, and rollback procedures
7. Translate medical affairs, commercial analytics, and clinical ops requirements into agent component specifications
8. Apply 21 CFR Part 11 auditability, HIPAA-compatible data handling, and GxP traceability patterns to every component
9. Build intelligent document processing pipelines for pharma content: drug labels, clinical study reports, HEOR dossiers, and regulatory submissions
10. Contribute to KOL mapping, competitive intelligence, and signal detection agents with domain-aware retrieval and reasoning strategies
11. Serve as the day-to-day technical reference for AI Engineers on the pod: code review, design feedback, unblocking implementation issues
12. Lead component-level design reviews and surface architecture risks before they reach staging
13. Pair with junior engineers on hard problems and document patterns and decisions in the team's shared knowledge base
14. Represent engineering quality in client-facing technical discussions and translate complex trade-offs into plain language
15. Contribute reference implementations and guardrail templates to the firm's internal agentic AI playbook

📌 Lead AI Engineer (Agentic Systems, Pharma domain) (Bengaluru)
🏢 Red Swan Labs
📍 Bengaluru