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03/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Data Engineer to help build next-generation data platform - the lakehouse foundation that will power data processing across the entire product. This is not a "write pipelines on top of someone else's platform" role, and it's not a pure infrastructure role either. It's both, deliberately.

You'll own the platform end to end: the infrastructure it runs on (Spark on Kubernetes, Apache Iceberg, AWS Glue, Airflow), the frameworks and tooling that let dozens of other engineers build on it without reinventing the wheel, and the design of the data pipelines themselves. Everything you build becomes leverage for the teams around you - your abstractions, base images, CI/CD flows, and operational patterns are what make the platform usable at scale.

You'll also own one of the hardest ongoing trade-offs in a high-scale data platform: balancing cost and performance. Compute sizing, storage layout, partitioning and compaction strategy, job scheduling - every decision has a price tag and a latency profile, and you'll be the one making those calls with data.

This role is ideal for an engineer who is equally comfortable debugging a Spark executor OOM on Kubernetes at 10am, designing a clean Python framework API at noon, and modeling the cost impact of a table layout change in the afternoon.



What You'll Do

Platform & Infrastructure

- Design, deploy, and operate our Spark-on-Kubernetes compute platform, including autoscaling, resource tuning, and multi-tenancy considerations.

- Own the lakehouse storage layer built on Apache Iceberg and AWS Glue catalog - table design, partitioning, compaction, schema evolution, and retention.

- Build and operate orchestration on Airflow: DAG standards, deployment flows, environment promotion, and reliability.

- Own production operations of the platform: monitoring, alerting, incident response, and continuous hardening.

Frameworks & Developer Enablement

- Build the code frameworks, libraries, and templates that other engineers use to write pipelines - so that spinning up a new production-grade Spark job is measured in hours, not weeks.

- Define and enforce standards for pipeline structure, testing, observability, and deployment across teams.

- Own CI/CD for data workloads: image builds, artifact promotion, and GitOps-based delivery.

- Act as a technical partner to product and research teams building on the platform - your customers are other engineers.

Data Pipelines & Architecture

- Design and build scalable batch and streaming pipelines processing complex, high-volume datasets from diverse sources.

- Lead large-scale backfills and migration initiatives, ensuring data consistency and integrity across evolving storage and compute platforms.

- Design event-driven data flows over large-scale queue systems (Kafka) for reliable, efficient data movement.

Cost & Performance

- Continuously balance cost against performance: right-size compute, tune queries and jobs, optimize storage layout and file sizes, and choose the correct engine for each workload.

- Build cost visibility and attribution into the platform so trade-offs are made with data, not guesswork.
דרישות:
- 5+ years of experience in software engineering, with meaningful time spent building and operating large-scale data platforms.

- Strong hands-on experience with distributed processing engines (Spark strongly preferred), including performance tuning and debugging in production.

- Practical experience deploying and operating workloads in Kubernetes-based environments - you're not afraid of infra work; you enjoy it.

- Experience building shared frameworks, libraries, or internal tooling used by other engineers, with the product mindset that comes with it (clean APIs, docs, versioning, backward compatibility).

- Strong proficiency in SQL and data modeling: complex analytical queries, query tuning, partitioning strategies.

- Solid software engineerin המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Architect to help define and evolve the data architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable data systems, set technical direction for how data is ingested, modeled, stored, and served, and guide teams in making high-quality architectural decisions that balance delivery speed with long-term sustainability.
This is a hands-on, senior technical leadership role: you will spend most of your time shaping data architectures with teams, reviewing data models, pipelines and critical code, and driving shared standards and patterns across the organization, all in an advanced agentic environment.
Responsibilities:
Define and evolve the data architecture for key domains (ingestion, ELT/ETL, data modeling, storage, APIs, integration, observability, governance, and security), including owning the lakehouse/medallion architecture (bronze/silver/gold) and the data flows that move data across layers at scale.
Translate business and product requirements into pragmatic data designs, data contracts, and architecture roadmaps; create and maintain architecture artefacts (data flow/lineage diagrams, ADRs, reference implementations, modeling guidelines).
Evaluate design options and technology choices, articulate trade-offs, and lead decision-making with stakeholders; push forward the agentic mindset and implementation across the data platform.
Partner with squad leads and senior engineers to design data solutions, break down complex problems, and keep implementations aligned with the target architecture; participate in design/tech reviews to ensure NFRs (performance, scalability, data quality, resilience, security, operability) are addressed early.
Provide hands-on support where it matters most: spike and prototype critical data flows, review complex PRs, and help debug tricky production data and pipeline issues.
Collaborate with Product to shape technical feasibility, sequencing, and scope for data-driven roadmap items; communicate complex technical topics in simple language to non-technical stakeholders.
Define and promote data architecture principles, modeling conventions, coding standards, and reusable patterns (shared transformations, libraries, datasets, services) to reduce duplication and technical debt; drive adoption of shared platform capabilities (observability, CI/CD, orchestration, governance, DevOps tooling) across squads.
Ensure data architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, data quality, and incident response; identify areas of high technical debt or architectural risk and lead remediation initiatives; define and track technical KPIs tied to architecture decisions.
Act as a technical mentor for senior engineers and tech leads, fostering a culture of thoughtful design, documentation, and constructive technical debate; lead by influence- help teams make better decisions instead of making every decision for them.
Requirements:
8+ years of experience in software / data engineering, including several years in a senior / staff / architect role designing complex data systems.
Strong experience designing modern data platforms and distributed data architectures (lakehouse/warehouse, batch and streaming/event-driven patterns, robust data APIs).
Experience working with columnar/serialization data formats such as AVRO and Parquet, including schema evolution and storage trade-offs.
Experience with DBT and ELT management tools for building, testing, and maintaining transformation pipelines.
Experience with Apache Airflow (or comparable orchestration tooling) for scheduling and managing data workflows.
Experience working with Databricks (or Snowflake) and medallion architecture (bronze/silver/gold).
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role at our company: 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 youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.
Requirements:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the companys data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.

What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.
Requirements:
5+ years of experience as a Data Platform/Infra Engineer.
Proven track record of building and operating scalable data infrastructure specifically within Data Lake architectures.
Proven experience designing and operating large-scale data processing workloads on Kubernetes, including workload autoscaling with KEDA.
Strong proficiency in Python and SQL.
Hands-on experience with Infrastructure as Code, preferably Terraform.
Experience with managing a data orchestration platform such as Airflow or Prefect.
Experience with Snowflake.
This position is open to all candidates.
 
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10/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.
Requirements:
5+ years of experience in data engineering roles in B2B SaaS companies
Strong SQL and hands-on data engineering experience building production pipelines (dbt strongly preferred; orchestration with Airflow or similar).
Deep, practical Snowflake experience - warehouse management, performance tuning, cost control, and data modeling.
Experience building or maintaining a semantic / metrics layer, and a strong point of view on metric governance.
Hands-on work with LLM-powered data applications - RAG, text-to-SQL, agent orchestration, or similar. Snowflake Cortex (Analyst, Search, Agents) is a big plus.
A builder mindset paired with the judgment to set standards others follow.
Nice to have:
Experience leading a guild, chapter, or community of practice - or otherwise driving standards without direct authority.
Familiarity with reverse-ETL, streaming ingestion (Airbyte or similar), and BI tooling on a semantic layer (Omni, ThoughtSpot).
Exposure to GTM / RevOps data (CRM, product usage, call intelligence) and the ambiguity that comes with it.
Experience with MCP, Streamlit, or embedding AI into internal tooling.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer at our company, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how our company understands and improves its service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our company's engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how our company operates
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.
Requirements:
5+ years as a Data Engineer with production-grade Python and SQL
Solid data warehousing experience (e.g., Snowflake, Databricks, Redshift, BigQuery).
Hands-on AWS familiarity: Lambda, S3, SNS/SQS, Firehose, and related lake/ingestion patterns.
Platform mindset: reliability, observability, and systematic production debugging.
Terraform/IaC skills: read, modify, and ship changes for EKS-based deployments.
AI tooling fluency: Cursor/Claude as a primary workflow, can navigate unfamiliar codebases with AI assistance
Experienced with modern data stack tooling; DBT, Airflow, and Iceberg storage are a significant advantage, as is familiarity with AWS big data services and BI tools such as Looker or Tableau
Passionate about data and genuinely curious about technology - you're the kind of person who identifies a gap, designs a solution, and sees it through without being asked
A strong collaborator who thrives working across engineering and business teams, comfortable translating ambiguous business needs into precise, well-designed data models
Self-driven and comfortable navigating complexity independently - you bring clarity to hard problems and raise the bar for the people around you.
This position is open to all candidates.
 
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're building the data foundation that will power at massive scale. We're looking for a battle-tested Data Engineering Tech Lead who has built and scaled data infrastructure at companies where the bar is exceptionally high.
This is a ground-up, architect-and-build role. You'll own the entire data infrastructure layer - caching, indexing, storage architecture, scalability patterns - and set the standard for how data flows across the organization at scale.
What Youll be Doing:
Own and architect \entire data infrastructure from the ground up - storage, caching, indexing, and platform foundations.
Make the hard technology calls: which databases, caching layers, orchestration systems, and data patterns we adopt - and why - based on scale, performance, and long-term engineering excellence.
Drive data scalability across the engineering organization, partnering closely with platform, backend, and product engineers.
Lead hands-on - you design, you build, you review, you mentor.
Requirements:
10+ years in data engineering, with significant time spent at fast-moving, high-scale tech companies.
Deep expertise in database architecture across OLTP, OLAP, NoSQL, and columnar systems, including MongoDB/Atlas, PostgreSQL, Redis, Elasticsearch, ClickHouse, and Couchbase.
Proven hands-on experience with DAG-based workflow orchestration systems such as Apache Airflow, Temporal, Prefect, Dagster, or similar - designing, scaling, and operating complex pipeline workflows in production.
Hands-on with cloud-native data infrastructure (AWS/GCP/Azure) and deep experience with data lake platforms - Databricks, Snowflake, BigQuery, or similar - including streaming and batch pipelines at scale.
Hands-on experience with event-driven architectures and event sourcing patterns (e.g., Kafka, Kinesis, or similar), with strong command of distributed systems principles - partitioning, replication, consistency trade-offs.
Who You Are:
Exceptional communicator - able to lead cross-functional design and implementation, work fluidly with engineers, product managers, and senior stakeholders, and drive execution across organizational boundaries.
A true people person - thrives working alongside talented teams, leaves ego at the door, and brings a can-do attitude to every challenge.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy turning raw data into powerful insights and owning the full data lifecycle, this role is for you!
Responsibilities:
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
Design and architect data products, from ingestion to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.
Requirements:
5+ years of hands-on experience in data engineering and in building data products for analytics and business intelligence.
Experience working on data developments using AI tools and agentic workflows.
Strong hands-on experience with ETL orchestration tools (Apache Airflow), and data lake houses (Databricks is an advantage)
Vast knowledge in both batch processing and streaming processing (e.g., Kafka, Spark Streaming).
Proficiency in Python, SQL, and cloud data engineering environments (AWS, Azure, or GCP).
Familiarity with data visualization tools (Power BI, Looker, or similar).
BSc in Computer Science or a related field from a leading university
Nice to have:
Experience working on early-stage projects, building data systems from scratch.
Background in building operational analytics pipelines, in which analytical data feeds real-time product business logic.
Experience in cost optimization in modern cloud environments.
Knowledge of data governance principles, compliance, and security best practices.
This position is open to all candidates.
 
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16/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.
Requirements:
4+ years in backend data engineering or infrastructure-focused software development.
Proficient in Python, with experience building production-grade data services.
Solid understanding of SQL
Proven track record designing and operating scalable, low-latency data pipelines (batch and streaming).
Experience building and maintaining data platforms, including lakes, pipelines, and developer tooling.
Familiar with orchestration tools like Airflow, and modern CI/CD practices.
Comfortable working in cloud-native environments (AWS, GCP), including containerization (e.g., Docker, Kubernetes).
Bonus: Experience working with GCP
Bonus: Experience with data quality monitoring and alerting
Bonus: Experience with Snowflake, DBT, Flink, Kafka
Bonus: Strong hands-on experience with Spark for distributed data processing at scale.
Degree in Computer Science, Engineering, or related field.
This position is open to all candidates.
 
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27/07/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
What you'll be doing:

Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.
Requirements:
What you'll need:

6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8756345
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior Software Engineer on the Cortex Platform Application team, you will be a hands-on technical leader responsible for designing, building, and operating critical backend platform services used across Cortex. This role is for an engineer who can combine deep platform/backend expertise with strong ownership, practical execution, and cross-team influence. You will help build scalable and reliable services, guide technical decisions, improve engineering methods, mentor engineers, and raise the quality of how the team designs, ships, documents, tests, and operates its systems. The team owns a broad set of platform capabilities, including areas such as application configuration, dashboards and reporting infrastructure, metrics, multi-tenant and MSSP infrastructure, log forwarding, notifications, auditing, access and permission engines, filtering and querying infrastructure, and other shared application platform domains. We are looking for someone who is not only strong technically, but also enjoys joining a high-performing team, taking ownership from within, and helping turn strong execution into repeatable engineering practice. A successful candidate will quickly become a trusted part of the team by shipping meaningful work, learning the team's domains, and helping others move faster. Over time, this person will help the team increase delivery capacity while also improving how work is designed, documented, tested, operated, and shared across the organization. The right person will not act as an external advisor or abstract architect. They will join the team's day-to-day work, earn trust through execution, and help create organized technical influence from inside the team.
Key Responsibilities
Design, build, and operate scalable, reliable, and secure backend services for the Cortex Platform.
Act as a hands-on technical leader, writing and reviewing production code for critical platform services.
Lead technical design for complex backend and platform domains, balancing long-term architecture with practical delivery.
Own and improve core platform capabilities used by internal engineering teams and Cortex customers.
Drive operational excellence, including observability, monitoring, alerting, incident response, reliability, and participation in on-call.
Improve engineering methods around documentation, testing, design reviews, ownership models, and production readiness.
Mentor senior, mid-level, and junior engineers through design guidance, code reviews, production work, and day-to-day collaboration.
Collaborate closely with product managers, architects, security experts, QA, DevOps, and other engineering teams.
Help internal customers use platform capabilities correctly by creating clarity, alignment, and practical technical guidance.
Identify gaps in systems, processes, and ownership, and lead improvements without adding unnecessary process or friction.
Contribute to a calm, practical, low-ego engineering culture focused on ownership, execution, and continuous improvement.
Requirements:
5+ years of professional experience in backend/platform software development.
Strong hands-on experience with backend development using languages such as Go, Javascript, C++, C#, Ruby, Python, or similar.
Proven experience designing, building, and operating large-scale distributed systems in production.
Strong understanding of software architecture, data modeling, APIs, reliability, observability, and production operations.
Experience working in cloud-based environments.
Ability to lead technical decisions while staying close to the code and implementation details.
Strong ownership mindset, including accountability for production behavior, quality, and long-term maintainability.
Experience mentoring engineers and raising technical standards within a team.
Strong communication skills and ability to influence across teams without relying on authority.
Practical, collaborative, low-ego working style.
This position is open to all candidates.
 
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עדכון קורות החיים לפני שליחה
8781540
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