Our Why At Dotmatics

At Dotmatics, a Siemens company, we believe science, data, and decision-making must be deeply intertwined for innovation to thrive. Our Portfolio includes Luma, LumaLab Connect, ELN Platform, Graphpad Prism, Geneious, SnapGene, Protein Metrics, OMIQ, FCS Express, LabArchives, NQuery, EasyPanel, SoftGenetics and Virscidian.

We have a vision for a new Lab of the Future that will change the future of scientific research.

We have created the world’s most comprehensive digital science platform – best-of-breed software applications already used by more than 2 million scientists, together in a single ecosystem united by a powerful, flexible enterprise data platform. This is not flat data buried away in digital graveyards. This is dynamic, multi-dimensional decision-making.

Scientific enterprises need a new level of effectiveness to achieve tomorrow’s breakthroughs. Illness will not wait. The biosphere will not wait. We are tireless in our vision, because the time for innovation is now.

Shaping the Future of Science At Dotmatics

Our global team of more than 800 colleagues are dedicated to supporting our customers in over 180 countries. Together, with our scientific community of users, we accelerate scientific innovation in order to make the world a healthier, cleaner, and safer place to live.

You’ll join a collaborative, global team pushing the boundaries of scientific innovation. Your ideas and efforts will have a tangible impact, accelerating scientific progress and discovery. We offer a dynamic, remote-friendly environment that fosters high integrity and collaboration, empowering you to excel. Dotmatics is a company built by scientists, for scientists. Combined, we are now the world’s largest cloud-based scientific research R&D platform. We need your help to keep growing and pioneering the future.

We are Science Driven. We are Customer Centric. We are Better Together.

What do we need

We are looking for an experienced and highly skilled Software Engineer (Agentic AI), to build the AI agent at the core of Dotmatics Luma platform. You will own the agent end to end: how it reasons, which tools it uses, what it remembers, how it recovers from failure, and how we know it is working. You will work in a small, high-trust engineering team alongside Product, scientists, and the wider Dotmatics organisation.

This is also an AI-native engineering role. Your success won’t be measured by how many lines of code you write. It will come from how well you decompose work for coding agents, give them the right context, tools, and constraints, verify their output with tests and review, and ship production software faster than a traditional senior engineer without lowering the quality bar. Coding agents are your default path for implementation, and you stay accountable for architecture, correctness, security, and review.

We want someone who thinks like the engineers who build frontier AI products: rigorous about quality, curious about how agents fail, and quick to adapt as models improve. You use AI tools daily to build AI tools, and you ship agents that work in production, not just in demos.

This position will require at least 1 day per week in office in Boston

In this role you will get to

Develop the agent itself: the loop, harness, and control flow connecting the model, tools, and state, including subagents, long-running tasks, checkpointing, and recovery.
Practice context engineering: decide what goes into the context window, when to compact or summarize, and how to keep the agent coherent over long-running experiments.
Design tools for the agent, with clear interfaces and descriptions, covering instrument orchestration, scheduling, data capture, and developer tooling such as GitHub, repositories, CI/CD, and workflows.
Give the agent memory and state persistence so it learns from and builds on earlier work.
Implement permissions and sandboxing that define what the agent can do on its own, what needs human approval, and how mistakes are contained.
Defend the agent against prompt injection and untrusted content, with auditability and data isolation suited to regulated environments.