Scientific Software Engineer (Full Stack)

Overview

Axle is seeking a Scientific Software Engineer that will develop the integration middleware and interactive interfaces for the SOM Center. This position involves building cloud-native applications that establish interoperability between cloud-based AI services, legacy laboratory systems, and real-time experimental state systems, delivering a unified data management interface for scientific discovery data.

Responsibilities

• API Development: Design and implement high-concurrency asynchronous APIs (using GraphQL or gRPC) to stream data between cloud inference endpoints (e.g., Vertex AI) and centralized state stores.


• AI-Assisted Development: Actively utilize AI-assisted coding tools (e.g., GitHub Copilot) to accelerate feature implementation, unit testing, and debugging.


• User Portal & Visualization: Develop the SOM User Portal using modern frameworks to render interactive visualizations. Implement WebGL-based components (e.g., Deck.gl, PixiJS) to render high-density parallel protocol topologies and multi-omics heatmaps without performance degradation.


• Agentic AI Integration: Implement the application logic to support Agent-based workflows, connecting user-facing chat interfaces with backend reasoning engines. Handle complex interaction patterns such as tool execution loops, multi-step reasoning chains, and streaming responses to the user.


• LIMS Integration & Ontology Enforcement: Develop business logic to integrate modern microservices with Legacy Laboratory Information Management Systems (LIMS). Enforce Ontology Mapping at the user interface level to ensure all data entry adheres to the SOM controlled vocabulary.


• Real-Time State Store: Implement a high-frequency experimental state store using in-memory databases (e.g., Redis), utilizing WebSockets or Server-Sent Events (SSE) to power real-time dashboards that reflect experimental data states.


• Cloud-Native Patterns: Implement Cloud-Native design patterns to reliably consume outputs from asynchronous cloud operations and surface results to the user.


• Collaboration: Collaborate with AI researchers to create explainable interfaces for model predictions.

Required Qualifications

• Bachelor’s or master’s degree in computer science or software engineering with experience in full-stack development for data-intensive applications.


• Proficiency in modern Python backend frameworks (FastAPI, Litestar) and strongly typed frontend ecosystems (React/Next.js with TypeScript).


• Experience with WebGL-based visualization libraries (e.g., Deck.gl, PixiJS, or Plotly) for rendering high-density biological datasets.


• AI Productivity: Demonstrated ability to leverage AI-driven coding assistants and LLMs to increase development velocity and code quality.


• Experience deploying and debugging applications in Containerized Cloud Environments (Cloud Run, ECS, or Kubernetes).


• Preferred Qualifications


• Familiarity with Agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen) and implementing "Tool Use" patterns in applications.


• Experience with Event-Driven Architectures (Pub/Sub, Kafka) for coordinating hybrid workflows.


• Knowledge of Graph Database query languages (Cypher/Gremlin) and Real-Time/In-Memory databases (Redis).


• Familiarity with integrating applications with Enterprise Identity Providers (OIDC/SAML) and experience working in a biotech or LIMS environment.