Software Engineer - Data Platform

Hadrian - Manufacturing the Future

Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts.

We’re accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts.

Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond.

As a foundational software engineer on our data platform engineering team, you will lead the charge on building the AI and data infrastructure that powers Hadrian's autonomous factories. This means writing software to aggregate, store, and make sense of data — and building the intelligent systems that sit on top of it.

Examples of possible work include building RAG pipelines and vector search systems that give our AI models access to the right manufacturing knowledge at the right time, developing MLOps infrastructure to deploy and monitor production models, building software agents to get data off of machines, and creating certified datasets that enable operations research, machine intelligence, and business analytics at scale.

You will be challenged to think creatively and solve complex data and AI integration problems. You will work cross functionally with production experts, operations research scientists, software engineers, and machining specialists to develop novel solutions working toward fully automated factories.

• Scope, architect, implement, and deploy critical AI and data infrastructure applications that will drive revenue and make a positive impact in the world.

• Build and own RAG pipelines and vector search systems that enable intelligent retrieval of manufacturing knowledge across Hadrian's data estate.

• Design and manage MLOps infrastructure — training pipelines, model deployment, monitoring, and orchestration — so that ML and operations research models run reliably in production.

• Build and manage a robust data warehouse and write software to coordinate and deploy data pipelines.

• Conceptualize and own the data architecture for multiple large-scale projects.

• Create and contribute to data frameworks that span on-premises and cloud infrastructure, improving the efficacy of logging machine data, while working with data infrastructure to triage issues and resolve.

• Solve our most challenging machine data and AI integration problems, utilizing optimal ETL patterns, frameworks, query techniques, and retrieval architectures sourcing from structured and unstructured data sources.

• Collaborate with machine engineers, operations research scientists, product managers, and data scientists to understand data and AI needs, translating complex systems into tools people actually use.

• Get to build alongside an incredible team of software engineers, mechanical engineers, operators, and the best machinists/CAM programmers in the world.

• Have extensive experience shipping modern, data-centric applications (our data systems use Argo-Workflows, Dagster, Superset, Aurora, RDS, S3, and back-ends are Go and Python, with gRPC/Avro and Kafka as our messaging platform).

• Experience building AI infrastructure in production: RAG pipelines, vector databases (such as Pinecone, Weaviate, Chroma, or equivalent), embedding systems, or semantic search.

• Hands-on MLOps experience: owning the full lifecycle of ML models from training through deployment and monitoring (Sage Maker, Ray, MLflow, or equivalent).

• Have experience with IaC and Git Ops tooling (We use Terraform extensively and have centralized on Kubernetes/Argo/Helm).

• Extremely well versed with data querying techniques…