Senior Software Engineer II, AI Native, Experimentation & ML

Life360 is a company dedicated to keeping families connected through innovative technology. They are seeking a Senior Software Engineer II to design and build high-quality APIs and services for their experimentation platform and recommendation systems, leveraging AI as a core part of their engineering processes.

Responsibilities:

• Design and build high-quality APIs and services for our experimentation platform and recommendation/personalization systems — experiences that are reliable, performant, and genuinely useful to product teams and members
• Work with AI (Claude Code) as a first-class collaborator — your primary workflow involves orchestrating agents to create specs, generate code and tests, verify results, and perform reviews
• Help define and codify AI-Native engineering practices for the team, establishing playbooks the broader org can adopt
• Build across the backend stack as needed — shipping polished, performant, and reliable experiences to tens of millions of users
• Collaborate closely with product managers and data teams to turn complex user problems into elegant, scalable engineering solutions
• Contribute to architectural decisions, code reviews, and a culture of craft and continuous improvement
• Participate in on-call rotation and incident response
• Use agentic workflows to dramatically increase the delivery of strong outcomes — moving faster without sacrificing quality
• Mentor team members and contribute to team processes, technical standards, and help evolve the team's AI-native engineering practices
• Support performance, reliability, and accessibility across the features you own

Requirements:

• 6+ years of backend software engineering experience
• Strong proficiency with Java and Spring Boot (this is our primary stack)
• Experience with Apache Kafka or similar distributed streaming platforms
• Solid understanding of distributed systems concepts: consistency, fault tolerance, replication, and data durability
• Comfortable with cloud infrastructure (AWS preferred) and containerized deployments
• Heavy user of agentic workflows, understands research-plan-implement cycle but doesn't outsource thinking to agents
• At least 1 year of hands-on experience prompting, evaluating, and building with LLMs
• Growth mindset - You structure problems precisely, you learn quickly, you can show interest outside 'your lane', and you are always happy to try something new
• Collaborative approach - You communicate clearly, work well across teams, and value diverse perspectives
• Ownership mentality - You take responsibility for your work from design through production and beyond
• AI-native working style - You use AI tooling (Claude Code or equivalent) as a genuine development partner: delegating discrete tasks, reviewing outputs critically, and running parallel workstreams rather than hand-holding one agent at a time
• Thoughtful communication - You can explain technical tradeoffs and articulate ideas effectively
• Experience building or operating experimentation, A/B testing platforms or feature-flagging systems
• Experience supporting recommendation, personalization, or ML-serving systems (feature stores, online/offline pipelines, low-latency model serving)
• Background in stream processing frameworks (Kafka Streams, Flink)
• Experience with schema registries and schema evolution strategies
• Knowledge of Confluent Platform or Confluent Cloud
• Understanding of CI/CD patterns, GitHub Actions, and artifact management (Maven, Nexus)
• Experience with observability tooling (Prometheus, Grafana, DataDog)
• Previous work on ecosystems or integration tooling