דרושים » הנדסה » Backend Engineer

We're looking for a Software Engineer to join our core engineering team and help build the infrastructure behind one of the fastest-growing AI APIs. You'll work on systems that handle massive scale across a distributed microservices architecture running on AWS. You'll ship fast, take ownership of critical systems, and solve hard infrastructure problems as we grow.

This is a great role for an engineer who loves building ambitious systems from scratch, and wants to tackle the kind of scale and complexity challenges typically reserved for much larger companies.

What Youll Do

Design and build high-performance distributed systems

Design and implement backend infrastructure and API endpoints

Build and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors

Improve performance, monitoring, and reliability across the stack

Own core systems and contribute to key architectural decisions

Help shape a strong engineering culture focused on velocity and quality

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

OurCrowd is a global investment platform connecting accredited investors and institutions with vetted, early-stage startups and venture funds. Behind that platform sits a tech organization building the systems that power how thousands of investors discover, evaluate, and act on private-market opportunities. We're now expanding our Technology team with engineers who can build the next generation of AI-driven products at the core of our platform.

Why Join Us? This is a chance to build at the intersection of fintech and applied AI, not as a side experiment, but as the direction of the product. You'll design and ship production-grade backend and fullstack systems that sit at the heart of a real, global investment platform, while being hands-on building AI agents that teams across the company actually depend on: architecting scalable microservices in Node.js, putting LLMs and agentic tooling to work, and owning features end to end from design through deployment.
Because real users and real capital flow through our platform, your work ships and matters from day one. You'll get real ownership over the features you build, hands-on exposure to how we adopt agentic AI, and a front-row seat to the startup and innovation ecosystem we live inside every day. If you want to master cutting-edge AI tooling while solving hard distributed systems problems alongside a small, sharp team - this is the place to do it.
This role requires 3 days a week in-office with the technology team primarily based out of Tel Aviv. Since we are headquartered in Jerusalem, candidates based in and around Jerusalem are welcome to apply, provided they're comfortable with Tel Aviv as the team's main hub.

Responsibilities:

* Design, build, and ship production backend and fullstack features for OurCrowd's investment platform using Node.js and microservices
* Build and deploy AI agents and LLM-powered tools used in production across the company, from prototype to rollout
* Architect and maintain scalable microservices, integrating SQL and NoSQL data stores as needed
* Design agentic workflows and orchestration pipelines, using low-code tools (e.g. n8n, Make) alongside custom services where appropriate
* Own features end to end: design, estimation, implementation, testing, deployment, and monitoring
* Partner with product, data, and engineering teams to turn business and investor needs into technical solutions
* Evaluate emerging LLM frameworks and AI tooling to keep our stack current and production-ready
* Write clean, well-tested code and participate in code reviews to uphold team quality standards
* Troubleshoot issues across the stack, balancing delivery speed with the reliability a capital platform demands
* Help shape architecture, tooling, and best practices as the team scales its use of agentic AI

Interview Process:

* Recruiter phone call
* Take home assignment
* In-person interview with Manager
* In-person interview with Department Head
* In-person interview with HR
* References

We are seeking a Staff Developer to join our team and take a lead role in shaping the architecture, evolution, and reliability of our systems core services.
You will directly shape Apono's technical direction, keeping our architecture aligned with company strategy while pushing forward what's possible in access management and engineering excellence. This role means owning a roadmap that raises the bar on quality, scalability, and security across our platform, as we bridge the operational security gap for organizations running in the cloud.
What you can expct:
Shape the architecture and long-term technical direction of core services powering Apono's platform.
Own complex, ambiguous initiatives end-to-end, from problem definition through rollout, spanning one or more teams and systems.
Break down large, undefined problems into a coherent execution plan, and drive that plan to completion.
Partner with product, design, and other engineering teams as a technical authority, translating ambiguity into clear architectural decisions.
Balance rapid iteration with long-term system health, scalability, and security.
Raise the bar for engineering standards, code quality, observability, and operational excellence across the org.
Mentor senior and mid-level engineers through design reviews, technical deep-dives, and pairing.
Evaluate new technologies and propose architectural improvements that shape how Apono builds going forward.
Leverage AI-assisted engineering workflows to multiply your own impact and the team's.
See your technical decisions directly shape the platform's ability to scale with the business.

Build the dashboard security teams live in all day. You'll own the experience where customers actually do the work: dense inventory tables, identity and software graphs, and the policy builders that turn discovery into enforcement. This is data-heavy, detail-heavy product surface where performance and clarity matter as much as polish.

What you'll work on

Inventory and findings screens over large datasets - fast, filterable, URL-addressable table state.

Identity and relationship views that make a messy org legible.

Policy and rule builders: complex, stateful UI that has to stay understandable.

Our internal design system and its Storybook - the shared vocabulary every screen is built from.

The design-to-code pipeline: design tokens synced from Figma and enforced in CI.

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.

Our Identity Protection Product Group in Israel has grown into one of the highest-performing teams, driving significant ARR growth while tackling one of cybersecurity's hardest problems: identity posture at cloud scale. As a Senior Engineer on the Entities team, you'll own the full entity lifecycle - from scraping identity data across Active Directory, Azure, and cloud providers, through enrichment and risk scoring, to publishing millions of identity entities into our asset platform. Your systems are the foundation that detection rules, alert pipelines, and customer-facing dashboards all depend on. You'll tackle real-world scale challenges: processing massive volumes of identity data through complex dependency graphs, maintaining data consistency across distributed regions, and building new high-performance Go microservices to replace and extend legacy systems.

What You'll Do:

Own the entity enrichment pipeline - a DAG-based computation engine that calculates 100+ fields, risk scores, and privilege relationships for every identity entity.

Build and maintain data ingestion services that scrape Active Directory forests, process cloud assets from Azure/AWS via Kafka, and integrate third-party identity sources.

Design and develop new Go microservices as the team migrates performance-critical paths from Node.js/Java to Go.

Solve complex data pipeline challenges: dependency ordering, incremental computation, race condition handling, and cache invalidation at scale.

Publish entity data to our centralized asset graph (SDMF), ensuring correctness and freshness for millions of identities - Optimize system performance - reduce enrichment latency, improve throughput, and handle traffic spikes gracefully - Mentor and elevate engineering talent, sharing expertise in building production systems that work under pressure.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
Key Responsibilities:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

LLM optimization is a young field with no settled playbook, so the optimizations you invent here are genuinely new - and they ship into production, not a paper. And they matter: real enterprises run enormous volumes of LLM traffic and feel every wasted token, so the work you do lands on live customer requests and solves a problem they actually have. It's about as close to the frontier, and as close to the product, as engineering gets.

03What you'll do
Invent and ship optimizations. Design new strategies across every layer of a request - prompt and context compression, tool pruning, file and dev-command trimming, semantic caching, cache-prefix stabilization - and take them all the way to the hot path. Each one has to cut tokens on real traffic without degrading output.
Prove every win. Build the evals and the token/quality instrumentation that separate a genuine saving from a plausible-sounding one. An optimization only ships when the numbers back it.
Live in the caching trade-offs. Provider prompt caches only pay off on byte-stable prefixes, and a naive rewrite can cost more than it saves. Knowing exactly when an optimization actually wins - deterministic transforms, per-session decision pins, semantic dedup - is a lot of the job.
Build and own the gateway that runs them. The real-time proxy that carries production LLM traffic - streaming, retries, backpressure - executing every optimization on the live request path.
Keep it fast and deploy anywhere. Defend a tight latency budget on the hot path, and package the whole thing so it installs cleanly into any customer's cloud - AWS, GCP, Azure, containers, Kubernetes - and upgrades without drama.
Own systems end to end. From first commit to code serving live customer traffic - plus the spend-visibility and governance product built on top - with a direct line to the founders.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
?About the Role
We are looking for a Data Assurance Engineer with strong experience in data validation, automation, analytics testing, and large-scale event pipeline quality.
This role is focused on ensuring the accuracy, stability, and reliability of data across our analytics and security event systems. The ideal candidate will be responsible for building automated validations, investigating data discrepancies, monitoring data quality, and working closely with engineering, data, and product teams.
Responsibilities

* Design, build, and maintain automated validation processes for large-scale event pipelines.
* Validate end-to-end data flows across ingestion, processing, storage, and dashboard layers.
* Create SQL-based validations to verify event counts, unique devices, metadata accuracy, schema
* consistency, latency, and data freshness.
* Investigate discrepancies between production systems, staging environments, data warehouses, object
* storage, and customer-facing dashboards.
* Monitor event volume, data latency, anomalies, spikes, drops, duplicates, and missing data.
* Build and maintain CI/CD validation jobs using tools such as Jenkins or GitLab CI.
* Create clear automated reports, dashboards, and email summaries for validation results.
* Work closely with backend engineers, data engineers, QA teams, and product stakeholders to identify,
* report, and validate fixes for data quality issues.
* Support performance and scalability testing for analytics dashboards, queries, and data pipelines.
* Help improve internal data assurance processes, data observability, and production monitoring.