高级软件工程师

Joulea is a startup building a software platform that reduces energy consumption in commercial buildings. Buildings consume 40% of the total energy in the United States and emit over 10% more greenhouse gas emissions than the entire transportation sector combined - vehicles, trucks, aircraft, rail and ships. A significant portion of commercial building budgets are spent and wasted on energy usage. We use the aerospace industry's product lifecycle management principles in order to create a novel approach to apply them to commercial real estate. Joulea implements holistic, integrated optimization methods that redefine energy efficiency and reduce operating costs within commercial buildings.

We are an ATDC portfolio company backed by WeMarathon, with offices located at ATDC in Midtown Atlanta. Joulea is SOC 2 Type II compliant across all five Trust Services Criteria, reflecting our strong commitment to security, availability, processing integrity, confidentiality, and privacy. We are seeking team members who are excited to take an already high-performing, security-first platform to the next level as we continue to scale.

Job Description

We are seeking a Senior Software Engineer who will own and scale Joulea's core backend and platform systems to support 10,000s of users and power accurate, ML- and BEM-driven energy assessment for commercial buildings.

This is a hands-on senior engineering role focused on backend systems, distributed infrastructure, and production reliability, with responsibility for integrating machine learning and building energy models into a unified, scalable platform.

Responsibilities

• Design, build, and operate backend APIs and services using FastAPI (Python) to support user-facing applications
• Scale distributed systems that ingest, process, and serve large volumes of building, sensor, and energy data
• Integrate ML models and BEM workflows into production backend services
• Build and operate ML-enabled pipelines using tools such as PyTorch Lightning
• Utilize Orchestration tool like Apache Airflow
• Architect and operate platform infrastructure on AWS
• Deploy services using Docker and Kubernetes
• Implement observability, monitoring, and alerting to ensure production reliability
• Collaborate closely with frontend (TypeScript / React), ML, and product teams
• Drive architectural decisions balancing performance, cost, security, and scalability
• Remain deeply hands-on in production code and infrastructure

Requirements

• 6+ years of software engineering experience, with strong backend and platform ownership
• Expert proficiency in Python and backend frameworks such as FastAPI
• Experience building and operating distributed systems in production
• Strong background in machine learning and deep learning
  (computer vision experience is a strong plus)
• Experience designing ML infrastructure and data engines for training and inference
• Familiarity with integrating advanced models (LLMs, LVMs, RAG) into production systems
• Experience with AWS, Infrastructure as Code, and cloud-native architectures
  Solid understanding of networking, authentication, and access control
  Strong collaboration skills and comfort working across engineering, ML, and product teams

This Role Is for You If You

• Identify primarily as a platform / backend engineer
• Have shipped and scaled production systems
• Care deeply about reliability, correctness, and long-term system health
• Enjoy enabling ML and modeling teams through strong platforms
• Lead by doing and take responsibility for what runs in production

Technologies We Use

• Backend: Python, FastAPI
• Frontend: TypeScript, React
• ML / Data: PyTorch Lightning, Apache Airflow
• Infrastructure: AWS, Terraform, Docker, Kubernetes
• Storage & Data: PostgreSQL, S3

Benefits

• Competitive Salary
• Equity Compensation
• Full Health, Vision, and Dental Insurance
• Per Diem

Interested? Apply now!

Have questions about our hiring process? Email us at [email protected].

International applicants are welcome if they are currently eligible to work in the US, such as with OPT EAD, CPT, or in H-1B status.