About the Role

We’re hiring a Distributed Systems / Backend Engineer to serve as a key contributor on the core backend platform powering Emerald AI. This is a high-impact role: you will drive architectural decisions, introduce best practices, build foundational infrastructure, and help guide the evolution of our real-time energy intelligence engine.

You’ll work across ingestion, compute, storage, and system orchestration—designing components that must be highly reliable, resilient, and capable of operating at scale. As one of the early engineering hires, you’ll have a major influence on our stack, roadmap, and long-term technical direction.

We’re looking for talent ranging from mid-level to highly seasoned senior contributors with expertise in backend systems.

Key Responsibilities

• Build scalable and reliable services, and APIs, used by both internal teams and enterprise customers.
• Continuously optimize performance across GPU clusters, cloud infrastructure, and backend systems.
• Implement observability, reliability, and security best practices
• Proactively identify technical debt, performance bottlenecks, and strategic opportunities for architectural improvements
• Collaborate closely with engineers, product managers, and energy domain experts to translate system constraints into scalable solutions.
• Guide other engineers through technical design reviews, mentorship, and high-quality code standards.

Minimum requirements

• 5+ years of software engineering experience with a focus on backend or distributed systems development.
• Extensive experience designing, building, and maintaining microservices architectures and distributed systems at scale
• Advanced system design capabilities with demonstrated expertise in performance optimization, horizontal scaling, and high-availability patterns
• Solid understanding of system performance, profiling, and optimization.
• Experience with object-oriented programming languages such as but not limited to: Python, Go, or Java

Preferred requirements

• Experience with AI/ML frameworks or libraries (e.g., TensorFlow, PyTorch) and familiarity with MLOps tools or workflows for deploying machine learning models into production.
• Understanding of cluster resource management and scheduling systems (e.g., experience with Slurm or similar job schedulers) and principles of efficient resource provisioning for compute-intensive workloads.

What We Offer

• Make an impact. Solve the AI power bottleneck and shape how data centers scale sustainably.
• Join a world-class team of AI, cloud, software, and energy experts in a collaborative, low-ego environment.
• Build from 0→1. Influence strategy, GTM, org design, and customer/investor engagement from day one.
• Competitive pay + equity. Stock options let you share in the value you help create.
• Comprehensive benefits , including medical, dental, vision, and 401(k) matching.
• Flexible location. Work from D.C., Boston, or the Bay Area, with 1 WFH day/week.
• Backed by top investors , including Radical Ventures and NVIDIA.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation.

Emerald AI strives to respect the dignity and ‎independence of people with disabilities and is committed to giving them the same ‎‎opportunity to succeed as all other employees.

Inclusiveness is core to our culture at Emerald AI, and we strive to ensure you get the most from your interview experience. Emerald AI makes reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to the Talent team.