Senior Software Engineer II - AI-Native, Messaging
New
L
Life360Mobile App, Tracking Devices
US and CanadaFull-TimeSenior
Salary148000 - 216500 USD per year
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Job Details
- Experience
- 6+ years
- Required Skills
- AWSJavaKubernetesSpring BootApache KafkagRPCTerraform
Requirements
- 6+ years of backend software engineering experience.
- Strong proficiency with Java and Spring Boot.
- Production experience with Apache Kafka or a comparable distributed streaming platform (Pulsar, Kinesis, Pub/Sub).
- Solid grounding in distributed systems concepts: consistency, fault tolerance, replication, delivery semantics, and data durability tradeoffs.
- Comfortable with AWS (or equivalent cloud) and containerized deployments on Kubernetes.
- Hands-on experience with Terraform or comparable IaC for real, multi-environment infrastructure.
- Prompting excellence – give agents context, constraints, and expected outcomes.
- Critical validation – explain every line the agent wrote, identify where it succeeded and where it fell short, and correct it.
- Agentic decomposition – break ambiguous problems into discrete, verifiable sub-tasks that an agent can execute.
- Parallel workstreams – run multiple agents or sessions concurrently on independent tasks.
- Troubleshooting with AI, not around it – diagnose and recover when an agent hallucinates or produces incorrect code.
- Technical authority – understand underlying tech well enough to catch agent errors.
Responsibilities
- Design, build, and operate streaming services on Kafka, Spring Boot, and Spring Cloud Stream, directing agents to scaffold, test, and iterate, and owning the outcome end-to-end.
- Develop and manage Kafka connectors for data integration (DynamoDB, S3, NSQ, custom sinks/sources) and the SMT chains that keep them honest.
- Own schema management and evolution across Protobuf, Schema Registry, and multi-language code generation — including the Gradle/Nexus publishing pipelines that back it.
- Drive platform migrations (MSK → Confluent Cloud, NSQ → Kafka) including dual-cluster consumer patterns, VPC peering, and cutover playbooks.
- Build monitoring, alerting, and operational tooling (DataDog, PagerDuty, Prometheus) that catch problems before pages fire.
- Write infrastructure as code in Terraform, ship it through CI/CD, and participate in the on-call rotation and incident response for the services you own.
- Work AI-natively as the default mode of operation. Run multiple agents in parallel. Write prompts with real context and constraints. Review every diff like you wrote it yourself. Know when to throw the agent's output out and do it by hand.
- Evolve the team's AI-native practices — prompt libraries, evals, review rituals, and the guardrails that make all of it safe at production scale.
- Mentor teammates, raise the bar on technical standards, and contribute to the team's API design, data contracts, and integration patterns.
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