Senior Software Engineer, Training & Experimentation

Academic Key; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Job summary

Lightning AI, a leader in AI training and experimentation, seeks a Senior Software Engineer to scale backend systems across distributed workloads. You will design APIs, orchestrate workflows, and own production services while collaborating with product, research, and platform teams.

The role emphasizes reliability, observability, and engineering excellence in a fast-moving environment. The position is hybrid with London offices and a minimum of two in-person days, offering a chance to impact AI

Qualifications

• Extensive experience building scalable backend systems.
• Strong understanding of distributed systems, asynchronous processing, and APIs.
• Experience designing and operating production services at scale.
• Familiarity with cloud platforms (AWS, GCP, Azure) and container tech (Docker, Kubernetes).
• Proven ability to own large technical initiatives from architecture through production.

Responsibilities

• Design and build backend services powering AI tooling and orchestration.
• Develop scalable APIs and platform capabilities for tool use and workflow orchestration.
• Build reliable infrastructure for long-running, distributed AI workflows.
• Collaborate with product, research and platform teams to ship new capabilities.
• Improve platform reliability, observability, and performance as workloads scale.
• Evaluate architecture, processes, and tooling to raise engineering quality.
• Mentor engineers on system design, distributed systems, and backend best practices.

Skills

Go

Python

Rust

Distributed systems

APIs

Cloud-native architecture

Tools

Docker

Kubernetes

Job description

# Senior Software Engineer, Training & Experimentation**Lightningai** · LondonAbroad London✓ Link validatedWho We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. What We're Looking For The Training & Experimentation team at Lightning AI builds the platform that enables developers to experiment at scale and train their own intelligence. Whether customers are training foundation models, fine-tuning open-source models, launching distributed training jobs, or iterating on experiments, this team creates the infrastructure and developer experience that powers every stage of the AI lifecycle. We're looking for a Senior Software Engineer to help design and scale the backend systems that make AI development faster, more reliable, and easier to use. You'll work across distributed training infrastructure, workload orchestration, experiment management, developer tooling, and platform APIs while partnering closely with our Managed Infrastructure, Core Platform, and Optimized Compute teams. This is an opportunity to build systems that support real-world AI workloads at scale while shaping the developer experience used by researchers, startups, and enterprise AI teams around the world. This role is based in one of our San Francisco, NYC, or London office hubs, with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time. What You’ll Do Design and build backend services that power AI agent orchestration and execution. Develop scalable APIs and platform capabilities for tool use, workflow orchestration, memory, and state management. Build reliable infrastructure that enables long-running, distributed AI workflows. Partner with product, research, and platform engineering teams to bring new agent capabilities into production. Improve platform reliability, observability, and performance as customer workloads continue to scale. Evaluate and strengthen technical architecture, engineering processes, and developer tooling. Maintain high standards for software quality through testing, automation, continuous delivery, and proactive management of technical debt. Mentor engineers on system design, distributed systems, and backend engineering best practices What You’ll Need Extensive experience building scalable backend systems using Go, Python, Rust, or similar languages. Strong understanding of distributed systems, asynchronous processing, APIs, and cloud-native application architecture. Experience designing and operating production services at scale. Hands-on experience building backend platforms, developer tools, or infrastructure products. Familiarity with cloud platforms such as AWS, GCP, or Azure and container technologies including Docker and Kubernetes. Proven ability to take ownership of large technical initiatives from architecture through production. Commitment to software quality, automated testing, observability, and continuous delivery. Strong communication skills and the ability to collaborate effectively across engineering, product, research, and design teams. Ability to thrive in fast-moving, ambiguous environments while balancing technical excellence with product impact. Compensation We are committed to offering competitive compensation that reflects the value each tea