Scientific Software Developer – Materials

Enthought, Inc.; Austin (TX); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Hybrid work

Job summary

Enthought, Inc. is hiring a Materials Data Scientist / Scientific Software Developer to join our client-facing solution delivery team in Austin.

You will pair deep materials science and chemistry expertise with agentic AI coding tools to accelerate R&D decisions and bring innovative products to market faster. You will work on data exploration through model development to production software, designing end-to-end informatics solutions, and collaborating with client researchers and business

Responsibilities

• Design end-to-end materials informatics solutions spanning data, models, and user-facing applications.
• Work with AI coding assistants and autonomous agents to explore data, prototype models, build software, write tests, and document results.
• Decompose problems, provide domain context and constraints to agents, and produce clear, defensible results.

Job description

We are hiring a Materials Data Scientist / Scientific Software Developer to join our client-facing solution delivery team. You will pair deep materials and chemistry expertise with agentic AI coding tools to help industrial materials and chemical researchers make better, faster R&D decisions and bring innovative products to market sooner. The work runs from data exploration through model development to production software, on project teams that combine Enthought’s proprietary technology with the open-source scientific Python ecosystem. Enthought is a lean, automation-first company where every role works like an engineer, directing AI tools to automate routine work and focusing human judgment where it matters most.

Key Responsibilities

• Design end-to-end materials informatics solutions, applying deep knowledge of materials science, chemistry, and machine learning to translate client R&D problems into architectures spanning data, models, and user-facing applications.
• Work agent-first, using AI coding assistants and autonomous coding agents as your default way to explore data, prototype models, build software, write tests, and produce documentation.
• Direct AI agents like a technical lead. Decompose materials and chemistry problems into well-scoped tasks, give agents the domain context and physical constraints they need, write clear specifications, and iterate toward correct, defensible results.
• Solve complex research and product development problems in close collaboration with client researchers and business leaders.
• Build data-driven models, AI-based decision-support tools, and automated analysis pipelines, and assemble them into web-based software solutions involving GUIs, 2D and 3D graphics, and cloud computing.
• Design AI-enabled and agentic capabilities into client solutions where they add value: LLM-powered literature and data extraction, tool and function calling, retrieval over materials data, and evaluation harnesses. These are held to the same rigor as any other component.
• Apply judgment about where AI and generative approaches fit and where they do not, especially given the small, sparse, and noisy datasets typical of materials R&D, balancing speed against reliability and reproducibility.
• Take part in collaborative development practices including release planning, architecture reviews, code review, sprint planning, retrospectives, and daily standups, and interface directly with clients to define, demonstrate, and refine solutions.
• Handle client data and intellectual property responsibly, using AI tools only in approved, secure configurations.

What We Offer

• Meaningful impact. Your work directly advances scientific breakthroughs, from accelerating drug discovery to developing sustainable materials.
• A front-row seat to agentic AI. We are an automation-first company where every role directs AI tools, and you will help define how the industry puts them to work.
• World-class colleagues. You will work alongside some of the smartest, kindest scientists and engineers around.
• Continuous learning. Enthought’s training programs in Python, machine learning, and scientific computing are open to you.
• A global, collaborative culture across our Austin, Cambridge, and Tokyo offices.
• Flexible hybrid work based out of our Austin office.