6+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
Strong proficiency in Python
Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
Familiarity with AI concepts like RAG, embeddings, mixture-of-experts, prompt crafting, and LLM context engineering - an advantage
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
Qualification wording
6+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
Strong proficiency in Python
Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
Familiarity with AI concepts like RAG, embeddings, mixture-of-experts, prompt crafting, and LLM context engineering - an advantage
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
Education & alternatives
- Sharp problem-solving instincts and the ability to move fast without cutting corners
- Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
- Ready to work in an office environment most days of the week
Open 5 monthsWe first saw this posting 160 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
Jun 2, 2026160 days ago
Recorded sightings
121
Last seen by us
Nov 9, 2026
Employer says posted
May 27, 2026
Jun 2, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 160
854
Up longer than most. Similar jobs usually come down between day 8 and day 54.
Well past Lemonade’s usual: its jobs come down by about day 13.
From 38,591 similar postings that came down, and 5 of Lemonade’s. Coming down is not always a hire.
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Where the posting names them
- 6+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
- Strong proficiency in Python
- Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
- Strong proficiency in Python
- Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
- Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
- Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
- Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
- Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how Lemonade uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at Lemonade: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems
What you'll need
6+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
Strong proficiency in Python
Hands-on experience with relational and NoSQL databases, and at least one major cloud platform (AWS, Azure, or GCP)
Experience with training, testing, deploying, and monitoring real-time or near real-time ML models in production
Fluent with AI-powered development tools like Cursor and Claude Code, and genuinely curious about what's next in GenAI, LLMs, and AI agents
Familiarity with AI concepts like RAG, embeddings, mixture-of-experts, prompt crafting, and LLM context engineering - an advantage
Sharp problem-solving instincts and the ability to move fast without cutting corners
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field
Ready to work in an office environment most days of the week