At a Glance
- Tasks: Design, implement, and deploy cutting-edge AI systems for diverse customers.
- Company: Join Lightning AI, the creators of PyTorch Lightning, in a dynamic tech environment.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with innovative teams in major cities like NYC, San Francisco, Seattle, or London.
- Why this job: Make a real impact by solving complex AI challenges in a fast-paced setting.
- Qualifications: Strong software engineering skills, especially in Python, and customer engagement experience.
The predicted salary is between 70000 - 90000 £ per year.
About Lightning AI
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.
What We Are Looking For
We are seeking an experienced Forward Deployed Engineer to partner directly with customers to architect, build, and deploy production AI systems and workflows on Lightning AI’s platform. In this role, you will own the customer journey from early exploration through production deployment, translating ambiguous business goals into reliable, observable systems with clear quality, latency, scalability, and cost outcomes. This role sits at the intersection of software engineering, research engineering, AI infrastructure, product thinking, and customer engagement. You’ll work closely with customer engineering teams as well as Lightning’s internal product and engineering organizations to deliver production-ready AI systems that help customers realize value quickly and scale with confidence. This is a hands-on engineering role that combines software development, AI infrastructure, technical customer engagement, and product thinking. Successful candidates will be highly technical, customer-oriented builders who thrive in fast-moving environments and enjoy solving ambiguous, real-world AI systems problems. This role is based in one of our hubs (New York City, San Francisco, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company off-sites.
What You’ll Do
- Partner directly with customers to design, implement, and deploy end-to-end AI systems and workflows on Lightning’s platform
- Translate vague customer objectives into clear technical specifications, proof-of-concepts, and scalable production implementations
- Own customer technical engagements end-to-end, from early discovery and architecture through deployment, monitoring, and expansion
- Develop and maintain production-grade software systems and services using modern programming languages, with a strong preference for Python
- Build reliable, observable systems with strong attention to latency, throughput, quality, scalability, and cost efficiency in production environments
- Debug and optimize AI systems across inference infrastructure, model behavior, APIs, and distributed workloads to improve performance and reliability
- Work closely with customer engineering teams throughout the full lifecycle of AI deployments, including technical discovery, implementation, deployment, and scaling
- Collaborate cross-functionally with Lightning’s product and engineering teams to improve platform capabilities, influence roadmap priorities, and identify opportunities for reusable product improvements
- Navigate ambiguity with sound technical judgment, making thoughtful tradeoffs and selecting the right tools and approaches without introducing unnecessary complexity
- Demonstrate strong ownership and accountability in execution, with a commitment to delivering high-quality outcomes for both customers and internal teams
Required Qualifications
- Strong software engineering experience building and maintaining production systems in one or more general-purpose programming languages, with Python strongly preferred
- Experience working directly with customers in highly technical environments, such as Forward Deployed Engineering, Solutions Engineering, Applied AI Engineering, Technical Product Engineering, or related roles
- Familiarity with AI/ML pipelines and the lifecycle of model development, evaluation, deployment, and monitoring
- Experience deploying and operating production AI/ML systems in cloud or distributed environments
- Familiarity with modern AI infrastructure and tooling such as Docker, Kubernetes, APIs, model serving systems, or distributed inference workloads
- Strong communication and collaboration skills, especially when working through complex technical topics with customers, engineers, and cross-functional stakeholders
- Ability to translate business needs into technical solutions and drive projects from initial concept through production delivery
- Ability to execute effectively in ambiguous, fast-moving, high-growth environments
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
Nice-to-Haves
- Experience building, deploying, or optimizing large-scale AI/ML systems in production environments
- Experience with modern AI stacks and tooling such as vLLM, TensorRT, Ray, LangGraph, vector databases, or workflow orchestration systems
- Familiarity with inference optimization, distributed systems, or GPU-accelerated workloads
- Startup experience or experience operating in highly cross-functional environments
- Track record of rapidly shipping proof-of-concepts and production systems while maintaining strong engineering quality
- Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, AI, or a related technical field
Forward Deployed Engineer in London employer: Lightning AI
Lightning AI is an exceptional employer that fosters a dynamic and innovative work culture, where engineers are empowered to partner directly with customers and tackle real-world AI challenges. With offices in vibrant cities like New York City, San Francisco, Seattle, and London, employees benefit from a collaborative environment that encourages professional growth and offers unique opportunities to work on cutting-edge AI systems. The company prioritises employee development, providing access to modern tools and resources, while maintaining a strong commitment to delivering high-quality outcomes for both customers and internal teams.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed Engineer in London
✨Tip Number 1
Get to know the company inside out! Research Lightning AI, their products, and their culture. This way, when you chat with them, you can show off your knowledge and passion for what they do.
✨Tip Number 2
Practice your technical skills and be ready to showcase them! Whether it's coding challenges or system design discussions, being hands-on will help you stand out during interviews.
✨Tip Number 3
Network like a pro! Connect with current employees on LinkedIn or attend industry events. A friendly chat can sometimes lead to referrals, which can give you a leg up in the hiring process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Forward Deployed Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Forward Deployed Engineer role. Highlight your experience with AI systems, Python programming, and any customer-facing roles you've had. We want to see how your skills align with what we're looking for!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Include specific examples of projects where you’ve built or deployed production systems, especially in AI/ML. We love seeing hands-on experience that demonstrates your ability to navigate complex technical challenges.
Communicate Clearly:When writing your application, clarity is key. Use straightforward language to explain your past experiences and how they relate to the role. Remember, we’re looking for someone who can translate complex ideas into simple terms, just like you would with a customer!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us quickly and efficiently. Plus, it shows you’re proactive and keen to join the Lightning AI team!
How to prepare for a job interview at Lightning AI
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and AI/ML pipelines. Brush up on your knowledge of Docker, Kubernetes, and any other tools that might come up during the interview. Being able to discuss your hands-on experience with these technologies will show that you're not just familiar but also capable.
✨Understand the Customer Journey
Since this role involves direct customer engagement, it’s crucial to understand how to translate vague business goals into technical solutions. Prepare examples from your past experiences where you successfully navigated customer needs and delivered results. This will demonstrate your ability to own the customer journey effectively.
✨Prepare for Problem-Solving Scenarios
Expect to face some real-world problems during the interview. Practice articulating your thought process when tackling ambiguous situations. Think about how you would approach debugging or optimising an AI system, and be ready to discuss your decision-making criteria and trade-offs.
✨Showcase Your Collaboration Skills
This role requires working closely with various teams, so be prepared to discuss how you’ve collaborated in the past. Share specific instances where you worked cross-functionally to achieve a goal, highlighting your communication skills and ability to simplify complex technical topics for different audiences.
