דרושים » תוכנה » Senior backend Engineer (Applied AI)

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

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.

we are looking for a Senior AI Builder to take AI from a "promising demo" to real production systems that customers rely on - and that continue to work well over time. Our R&D group is a team of 12 engineers and one architect, spanning backend to mobile, building the accounting platform businesses actually run on every day.
What you'll do
* Build and ship LLM-powered AI capabilities to production- agentic flows, retrieval over our data, extraction from real-world documents, and more. Solutions need to be accurate, measurable, cost-efficient, and rollback-ready.
* Build and lead the evaluation process - continuously measure the quality of models and solutions, and be able to answer clearly: is the new version actually better than last week's?
* Own whatever it takes to get the solution into production- from AWS Lambda to Vue and PHP. You don't need to be an expert in every technology, but you should be comfortable getting into the code and solving problems wherever the work actually lives.
Why this is a real challenge - and why it's worth it Our customers trust us with their financial data. There's no room for "almost right" when it comes to the answers our systems provide, and we operate in an environment with significant regulatory requirements- including PCI-DSS, GDPR, and Israeli privacy law. The goal is to take AI capabilities, turn them into real products people can trust, and see them reach customers- at a company small enough that your work can ship this quarter, not next year.
Advantages:

* Experience with Databricks/Spark, Vue 3, fintech or another regulated domain, and significant experience with AI-powered development tools and agentic development.

As a Full Stack Engineer, youll help shape the brain and heartbeat of our product. This isnt a narrow coding role, youll own problems end-to-end, from first sketch to shipping, and watch your work come alive in production within weeks. Youll join a tight, ambitious team where every engineer helps define both the product and the culture.
What youll do
Work across the stack, from frontend polish to backend resilience.
Collaborate with product and design to shape features, not just code them.
Ship fast, ship often, and still take pride in craft.
Explore and integrate advanced AI (LLMs, GenAI) into a production-grade product.
Turn customer feedback into product improvements that stick.
How we work
In-office, side-by-side, with quick feedback and faster shipping.
Pragmatic and product-first: no feature ships unless it makes a real impact.
Supportive but demanding: we hold a high bar and help each other reach it.
The tools we use (today - youll help shape tomorrow)
Powering the logic that makes hardware data come alive in our backend is Python. On the frontend, React and TypeScript give users a simple, intuitive way to work with complex information. Everything runs in the cloud - AWS and GCP - with containerized microservices (and Kubernetes keeping the gears turning smoothly) ensuring we can ship fast and scale seamlessly. For intelligence, we weave in LLMs and data pipelines to unlock insights from documents. And for resilience, our real-time monitoring keeps an eye on the moving parts - so the system stays as reliable as the products it supports.

We're looking for our **first Forward Deployed Engineer**. You'll sit directly with our customers' engineering teams and get their workloads onto Impala - from the first scoping conversation to a production endpoint carrying real traffic, at a cost and latency profile they couldn't hit anywhere else.
This is an engineering role. You will write code every day, in customer repos and in ours. It also carries pieces of solutions architecture, product management, and pre-sales, and you should want that mix rather than tolerate it. Ambiguous business goals come in; observable, benchmarked, production services go out.
As the founding FDE you also define the function: what a POC looks like, what we promise and measure, which patterns get productized, and how the field feeds the roadmap. The next FDEs will work from what you build here.
What You'll Do
- **Own customer outcomes end to end:** problem framing, evaluation design, migration, deployment, benchmarking, monitoring. You're the technical owner from first call through expansion.
- **Win the POC:** turn a vague objective into a tight spec and a working proof of concept fast, with explicit quality, latency, throughput, and cost-per-token targets - and hit them.
- **Tune serverless inference for real workloads:** model and engine selection, batching strategy, KV cache behavior, speculative decoding, quantization, parallelism, cold-start and autoscaling behavior under bursty traffic. Diagnose regressions down to the inference engine.
- **Migrate workloads onto Impala:** move customers off OpenAI-compatible APIs, self-managed vLLM, SageMaker, or their own GPU fleets - and prove out the quality and cost delta with numbers.
- **Guide model strategy:** advise on open-weight model selection, distillation, and fine-tuning for specific tasks; help customers get from a general-purpose frontier model to a smaller, faster, cheaper one that holds quality.
- **Close the product loop:** bring the field back into the roadmap - write the PRDs, land the PRs, and turn one-off customer work into platform features.
- **Be the technical anchor in the room:** support sales on complex evaluations, run technical onboarding, earn trust with staff engineers and CTOs.

We are looking for a Staff engineer to join our Data Products team.

The team owns the data platform layer underneath our core operations.

It builds and operates the real-time data processing systems, quality pipelines, schema infrastructure, and knowledge base tooling that make agent-driven work trustworthy at scale.


What you'll be doing:
Design, build, and operate Flink-based streaming pipelines at production scale, the real-time processing systems at the core of our internal workflows.
Own data quality and observability infrastructure: schema contracts, freshness monitoring, ownership registries, and the alerting systems that catch problems before they affect downstream processes.
Build and evolve the knowledge base tooling that makes institutional context queryable for agents and engineers.
Drive data integrity work: design systems that recover reliably from failure and make the underlying platform trustworthy by default.
Collaborate with the Agentic Data Foundation initiative as we build a company-wide data layer; Data Products is where the proof of concept gets built and validated.
Set technical direction across the team's systems and hold architecture standards with the EM and other Staff engineers.

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 talented Software Engineer to join Appdome's Identity Group. You will take part in building advanced fraud detection capabilities, working closely with security researchers and data teams to develop cutting-edge solutions that protect hundreds of millions of mobile devices.
Responsibilities
* Design and develop core components of fraud detection systems from early prototyping through production-ready releases.
* Build scalable backend services and distributed systems that process data at scale.
* Work with large-scale datasets and collaborate with data teams to create actionable signals and features.
* Write high-performance, production-quality code in C and C++ optimized for reliability and performance.
* Take ideas from rapid proof-of-concept through to production, tackling complex engineering challenges across the full development lifecycle.

Anyone can ship an AI agent. Shipping one thats right ~98% of the time, with no human checking its work, takes different engineering. Thats what this team builds.
We're looking for a Senior Backend Engineer to help push our AI customer-service agents closer to fully autonomous insurance service. You'd be joining the team behind the agent that talks to real customers every day over email, phone, chat, and SMS - handling policy questions, claims conversations, and verified documents end-to-end, with no human in the loop. This isn't a demo or a copilot. Real customers, real money, real stakes, every day.
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 you'll
Design, build, and own production LLM agent systems end-to-end - deciding how the agent thinks, what it's allowed to do, and how it fails safely
Work on our real-time voice agent, where the hard problems are conversational: interruptions, mid-sentence tool calls, and keeping response times imperceptibly fast
Shape the next generation of our knowledge base - how the agent's knowledge is structured, curated, and served, so answers stay grounded as coverage grows
Ship changes as controlled experiments, measure them against thousands of replayed real conversations on our in-house eval platform, and graduate winners into production
Track cost per conversation across millions of LLM calls and find the wins that cut spend without cutting quality
Own what the model knows and says - the customer context it sees, the limits on what it may reveal, and the guardrails against confident nonsense
Build and operate scalable backend services in TypeScript/Node on Kubernetes/AWS with deep observability - if you ship it, you own it.

We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
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 you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

Forward Deployed Engineering sits at the frontier of that work. We embed with our most strategic enterprise customers, running on-prem, air-gapped, and heavily regulated environments, and own the technical arc from discovery through production.

Your day might include designing a solution architecture for a high-impact agentic use case, debugging a production routing issue deep in our codebase, deploying a new MCP server with a customer team, or aligning with a CTO on a rollout plan; all in service of outstanding outcomes and rapid time to value for the organizations we work with.

This is a founding function. The first FDEs will define how we conducts field engineering: the standards, playbooks, and technical bar. The work is hands-on, commercially scoped, and high-leverage: youll partner closely with Product, Research, Platform, Security, and GTM, and what you learn in production directly shapes what the core team ships next. If you thrive under ambiguity, make fast and sound decisions when the stakes are high, and get energy from closing the gap between what customers hit in production and what we build next, this role is for you.

In This Role You Will
Own technical delivery across multiple deployments from first prototype to stable production, including core engineering work that unblocks strategic accounts.
Lead deep technical diagnosis and remediation in our codebase and production environments, model routing and gateway behavior, large-PR scaling, multi-pass behavior, performance and reliability issues.
Build customer-specific extensions (MCP servers, agent skills, platform integrations) that deliver immediate value and become durable product capability; upstream them into the main roadmap where appropriate.
Embed closely with customer engineering teams: serve as their senior technical counterpart for hands-on debugging, architecture reviews, and joint implementation.
Scope work, sequence delivery, and remove blockers early; make deliberate trade-offs between scope, speed, and quality to protect delivery timelines.
Partner with Product, Research, and Platform to convert account learnings and eval-driven feedback into roadmap items, specs, and prioritized engineering work.
Codify working patterns into tools, playbooks, runbooks, and reproducible benchmarks that Support and account teams can operate independently and help scale the field engineering function across the organization.