At we are on a mission to transform how society cares for every older adult in need. We leverage the power of AI and data to ensure safety dignity and satisfaction in every caregivercare recipient interaction. If youre passionate about making a meaningful impact and want to help shape the future of elder care we invite you to join our team. Here youll be part of a culture that values innovation and compassion and youll find exciting opportunities for professional growth as we work together to create an ideal care environment for older adults.
About The Role
As a Senior Platform Engineer at you will build the shared backend platform and AI enablement layer that every product team builds on top of and you will be a key design partner across R&D - helping teams shape architectures for new AI-powered features backend services and agentic systems.
This is a force-multiplier role: instead of shipping one product feature you raise the velocity and quality of every team. You will make key architectural decisions about how AI is integrated how services communicate and how engineers measure and improve what they ship - and you will coach and review designs across the org so we move fast without compromising on quality.
What Youll Do
Lead and partner on architecture and design across R&D - running design reviews shaping technical proposals and helping teams choose the right patterns for AI backend and data-driven systems
Design and build core backend platform services and SDKs (auth eventing feature flags configuration data access) that product teams compose into AI-powered features
Build the AI enablement layer: shared LLM gateways prompt and agent frameworks evaluation and tracing tooling model routing guardrails and cost/latency controls - so every team can adopt LLMs and agents safely and consistently
Define and own platform processes that improve engineering velocity and quality: service templates paved-road patterns code review standards release workflows and golden-path documentation
Build the observability and quality story for AI features end-to-end: structured logging metrics distributed tracing LLM-call instrumentation prompt/response evaluations and regression detection
Research prototype and lead the selective adoption of new AI tooling agent frameworks and backend technologies into the platform
Requirements:
4 years of experience in backend / software engineering with proven experience designing and developing high-performance distributed systems
Strong proficiency in Python and
Proven experience working in cloud environments (AWS preferred; GCP/Azure acceptable)
Hands-on experience with microservices containerized environments (Kubernetes) and CI/CD pipelines (GitHub Actions)
Experience with message queuing and streaming systems such as Kafka and/or SQS
Strong understanding of SQL and NoSQL databases large-scale data flows and data-driven systems
Experience in developing and deploying LLM agents to production (via Langgraph Langchain etc.)
Strong collaboration and communication skills both Hebrew & English
At we are on a mission to transform how society cares for every older adult in need. We leverage the power of AI and data to ensure safety dignity and satisfaction in every caregivercare recipient interaction. If youre passionate about making a meaningful impact and want to help shape the future of...
At we are on a mission to transform how society cares for every older adult in need. We leverage the power of AI and data to ensure safety dignity and satisfaction in every caregivercare recipient interaction. If youre passionate about making a meaningful impact and want to help shape the future of elder care we invite you to join our team. Here youll be part of a culture that values innovation and compassion and youll find exciting opportunities for professional growth as we work together to create an ideal care environment for older adults.
About The Role
As a Senior Platform Engineer at you will build the shared backend platform and AI enablement layer that every product team builds on top of and you will be a key design partner across R&D - helping teams shape architectures for new AI-powered features backend services and agentic systems.
This is a force-multiplier role: instead of shipping one product feature you raise the velocity and quality of every team. You will make key architectural decisions about how AI is integrated how services communicate and how engineers measure and improve what they ship - and you will coach and review designs across the org so we move fast without compromising on quality.
What Youll Do
Lead and partner on architecture and design across R&D - running design reviews shaping technical proposals and helping teams choose the right patterns for AI backend and data-driven systems
Design and build core backend platform services and SDKs (auth eventing feature flags configuration data access) that product teams compose into AI-powered features
Build the AI enablement layer: shared LLM gateways prompt and agent frameworks evaluation and tracing tooling model routing guardrails and cost/latency controls - so every team can adopt LLMs and agents safely and consistently
Define and own platform processes that improve engineering velocity and quality: service templates paved-road patterns code review standards release workflows and golden-path documentation
Build the observability and quality story for AI features end-to-end: structured logging metrics distributed tracing LLM-call instrumentation prompt/response evaluations and regression detection
Research prototype and lead the selective adoption of new AI tooling agent frameworks and backend technologies into the platform
Requirements:
4 years of experience in backend / software engineering with proven experience designing and developing high-performance distributed systems
Strong proficiency in Python and
Proven experience working in cloud environments (AWS preferred; GCP/Azure acceptable)
Hands-on experience with microservices containerized environments (Kubernetes) and CI/CD pipelines (GitHub Actions)
Experience with message queuing and streaming systems such as Kafka and/or SQS
Strong understanding of SQL and NoSQL databases large-scale data flows and data-driven systems
Experience in developing and deploying LLM agents to production (via Langgraph Langchain etc.)
Strong collaboration and communication skills both Hebrew & English