Associate AI Engineer in LAUNCH program developing AI solutions. Collaborating with teams and working post - training on client projects.
About the role
- Senior AI Engineer building agentic systems for pharmaceutical teams using AI technologies. Designing and implementing multi-agent architectures and backend services with real production stakes.
Responsibilities
- Own and evolve the agentic layer that powers our products
- Design and build the multi-agent orchestration systems, RAG pipelines, tool-use architectures, and workflow engines
- Make foundational architecture decisions and shape engineering standards
- Work directly with product and leadership from day one
- Design and implement multi-agent architectures using Agno, LangChain, and LangGraph
- Build and maintain scalable backend services and APIs in Python and FastAPI
- Own agent orchestration logic: task routing, tool use, state management, and human-in-the-loop integration
- Design and implement RAG pipelines over domain-specific data, with strict requirements for accuracy, traceability, and compliance
- Make production-grade decisions on LLM integration, prompting strategies, and reliability patterns
- Set engineering standards for code quality, testing, and deployment of agentic systems
- Drive end-to-end feature ownership from design through to production
- Mentor engineers and actively shape the engineering culture as the team grows
- Collaborate closely with product and leadership to influence the technical roadmap
Requirements
- A strong Python engineer who has shipped production systems, not just prototypes
- Hands-on with agentic frameworks (LangChain, LangGraph, Agno, or similar)
- Fluent in LLMs in production: prompting, tool use, orchestration, failure modes
- Experience building production RAG systems: retrieval architectures, vector databases, embedding strategies, and evaluation frameworks
- Experience with agent evaluation frameworks and observability tooling (e.g. LangSmith or similar): tracing agent behavior, debugging multi-agent interactions, and ensuring reliability in production
- Comfortable with cloud environments (AWS, GCP, or Azure) and distributed system design
- Experienced with MLOps practices: CI/CD, monitoring, deployment pipelines
- Autonomous, low ego, and serious about what you build
- Excited about working in a domain where the quality of your work has real-world consequences
- Nice to have:
- Experience in life sciences, regulated industries, or GxP-compliant environments
- Experience with multi-agent systems and workflow orchestration
Benefits
- A competitive compensation package
- A flexible working culture because your work-life balance matters to us
- A position that enables you to have an impact on 1’000s of people, and the whole company's growth.
- An international, knowledgeable, and passionate team with a strong collaborative mindset
- Employee Stock Ownership Plan
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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