Overview
Senior technical contributor designing, building, and integrating agentic AI and scientific AI workflows to accelerate scientific discovery.
What you'll do
- Design and implement agent-based systems for complex scientific workflows.
- Develop reusable components for orchestration, context/memory handling, and workflow planning/execution.
- Integrate foundation and scientific AI models into end-to-end workflows (including APIs/services/interfaces).
- Build knowledge-driven AI systems using retrieval, vector databases, knowledge graphs, and Graph-RAG.
- Develop end-to-end workflow patterns that combine ingestion, retrieval, inference, orchestration, and scientific analysis.
- Create evaluation frameworks for accuracy, reliability, scientific relevance, hallucination rates, and workflow effectiveness.
- Partner with scientific and engineering stakeholders to translate research needs into technical solutions.
What you'll need
- Strong engineering background in AI and machine learning systems.
- Hands-on experience developing AI/ML solutions.
- Expertise in Python and modern AI/ML development frameworks.
- Experience designing/implementing production-quality software systems.
- Understanding of ML lifecycle and evaluation.
- Knowledge of distributed systems and scalable architectures.
- BS or MS in Computer Science, Engineering, Computational Biology, Bioinformatics, or related field.
Nice to have
- Experience with LLMs, agentic AI systems, and workflow orchestration.
- Experience with RAG, vector databases, and knowledge-driven AI architectures.
- Experience integrating scientific or domain-specific AI models.
- Familiarity with cloud AI platforms (AWS Bedrock, SageMaker, Azure AI, or equivalent).
- Familiarity with knowledge graphs, Graph-RAG, or scientific knowledge systems.
- Experience working closely with researchers and domain experts.
Details
- Preferred: Bachelor's with 5–9 years of experience.
Read the full description and apply on the company’s own careers page.
