דרושים » תוכנה » Solutions & Integrations Engineer

We are looking for a detail-oriented and technically skilled Senior QA Engineer to join our engineering team and help ensure the quality, reliability, and security of our product.
In this role, you will own the quality of complex cybersecurity features from design through production, working closely with developers, product managers, and automation engineers. You will play a key role in defining test strategies, identifying risks early, and ensuring high-quality releases.
As part of your daily workflow, you will leverage AI-powered tools to improve test planning, discover edge cases, investigate defects, analyze logs, and enhance overall testing efficiency.
The Responsibilities:
Own the automation domain end-to-end: strategy, architecture, implementation, and continuous improvement
Design, build, and maintain scalable test automation frameworks across UI, API, integration, and system layers
Develop hands-on automation code in Python and/or TypeScript
Drive quality standards across engineering teams, partnering closely with developers, QA, DevOps, and product stakeholders
Define and implement automation best practices for reliability, scalability, maintainability, and fast feedback
Integrate and optimize automation within CI/CD pipelines to enable rapid, confident releases
Test complex SaaS, cloud, and cyber-related product flows, including security-sensitive scenarios, permissions, integrations, and system behavior
Use AI tools to support automation development, test generation, debugging, log analysis, documentation, and coverage improvement
Proactively identify coverage gaps and improve system testability, observability, and debuggability
Participate in system design and feature planning to embed quality from the earliest stages
Build and evolve testing environments using scripting, infrastructure-as-code, and cloud-native tools
Mentor and guide engineers, elevating automation standards across the organization

We are seeking an AI Full-Stack Developer to build and scale automation solutions across internal company processes using AI, LLMs, and agent-based systems. This role focuses on delivering practical automation solutions, integrating AI capabilities with internal tools, and orchestrating workflows across multiple systems, with a dynamic range of tasks that offer both quick wins and complex challenges.

Responsibilities:

Build AI-driven automation solutions using LLMs, APIs, and agent frameworks.
Develop systems to automate document processing, data extraction, and operational workflows.
Design and implement multi-step automated workflows connecting AI models and internal services.
Integrate automation solutions with internal systems such as HR, finance, legal, dashboards, and ticketing tools.
Deliver and iterate practical automation solutions swiftly, from simple GPT/AI integrations to complex workflows.
Train and support internal teams on newly built or optimized systems for strong adoption and self-sufficiency.
Collaborate with Technical Team Lead, Product Manager, and IT teams on architecture and system integration.
Communicate clearly with internal stakeholders and external partners or vendors.

We are currently expanding our R&D center in Tel Aviv, where we are building advanced data systems, automation infrastructure, and intelligent workflows that power our products and enable the next wave of innovation in advertising technology.

This role focuses on building reliable data systems and automation infrastructure, while helping us introduce AI-driven and agentic automation capabilities that improve how our engineering and data platforms operate.

What You Will Do
Design and build backend services using Node.js and TypeScript
Develop and maintain data pipelines and automated workflows
Work with Snowflake, MongoDB, and large datasets
Improve reliability and performance of data processing systems
Build and maintain automation infrastructure that supports data and platform operations
Design systems that help automate engineering and data workflows
Write unit and integration tests for backend services and workflows
Collaborate with analysts and product teams to translate complex workflows into scalable systems
Participate in improving engineering standards, testing culture, and development practices
Drive the next generation of automation across the platform by designing AI-driven and agentic workflows that enhance how our engineering and data systems operate
Your Day-to-Day Work
Developing backend services and APIs
Optimizing queries and data processing workflows
Building reliable systems for processing large-scale data
Designing and implementing automation processes across data and engineering workflows
Supporting AI-driven and agentic automation initiatives across internal systems
Writing automated tests to ensure system stability
Collaborating with engineers in Israel and global teams

Who We're Looking For - The Dream Maker We’re looking for a hands-on Onboarding & Implementation Lead to own and scale the onboarding experience across both SMB and Enterprise customers. This highly customer-facing role combines implementation project management, customer consulting, operational excellence, and technical problem-solving. You’ll guide customers from contract signature through successful activation, ensuring they overcome blockers, complete their implementation, and realize value quickly and confidently. You’ll lead Enterprise onboarding engagements, support complex SMB implementations, and proactively drive onboarding completion across our broader customer base. This is a role for someone who can manage complex customer projects while also improving the systems, processes, and playbooks behind them. About Chargeflow Chargeflow is a leading force in fintech innovation, tackling chargeback fraud and the impact it has on online businesses. Born from a deep passion for technology and eCommerce, we’ve developed an AI-driven solution that helps merchants manage credit card disputes, recover lost revenue, and protect their businesses through a unique success-based model. Backed by $49M from Viola Growth, OpenView, Sequoia Capital, and other top-tier global investors, Chargeflow is on a product-led growth journey. We’re a tight-knit team of passionate builders and entrepreneurs, united by our mission to revolutionize eCommerce and protect online businesses from chargeback fraud. What You’ll Own
* Lead onboarding and implementation projects for Enterprise customers from contract signature through activation and first value.
* Serve as the primary customer point of contact throughout the implementation journey.
* Build and manage onboarding plans, timelines, milestones, risks, dependencies, and stakeholder communication.
* Lead customer meetings with both operational and executive stakeholders, creating clarity, accountability, and momentum.
* Support complex SMB implementations that require additional guidance or technical assistance.
* Act as an escalation point for onboarding challenges, identifying root causes and coordinating the right teams to remove blockers.
* Proactively monitor progress across active onboarding accounts and drive customers toward completion and activation milestones.
* Reduce onboarding drop-off and improve completion rates, implementation timelines, and time to value.
* Continuously improve onboarding workflows, playbooks, documentation, and customer communications.
* Identify opportunities to automate manual work, increase operational efficiency, and improve visibility into onboarding status and risks.
* Partner closely with Customer Success, Sales, Product, Engineering, and Support to deliver a seamless customer experience.
* Surface recurring implementation challenges and customer friction to internal stakeholders, helping shape product and process improvements.
* Develop expertise across Chargeflow’s payment ecosystem, including Stripe, Shopify Payments, PayPal, Adyen, and other payment providers.
* Help customers understand dispute-management best practices based on their business model, payment setup, and merchant vertical.

What will you do:
Design, build, and maintain production-grade AI-powered applications and services.
Develop end-to-end full-stack solutions, including backend services, APIs, and modern React-based frontends.
Build scalable, secure, and highly available distributed systems.
Develop AI agents, copilots, autonomous workflows, and intelligent automation.
Build and deploy RAG (Retrieval-Augmented Generation) solutions and integrate LLMs into production.
Design AI orchestration workflows using frameworks such as LangChain, LangGraph, or similar.
Implement AI evaluation, tracing, and observability pipelines using Langfuse or equivalent tools.
Develop MCP (Model Context Protocol) integrations and AI tooling ecosystems.
Build and maintain cloud infrastructure, CI/CD pipelines, and Infrastructure-as-Code.
Drive engineering productivity through AI-assisted development and automation.
Collaborate closely with Product, Design, and Engineering teams to deliver customer value.
Research and evaluate emerging AI technologies and introduce innovative solutions.
Own features end-to-end-from architecture and development to deployment, monitoring, and continuous improvement.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

we are looking for a Experienced AI Software Engineer.
You are a Senior AI Software Engineer looking to join a GenAI Infrastructure team and build production-grade GenAI capabilities and the infrastructure behind them. You will be a hands-on engineer focused on AI agents, RAG pipelines, tool-calling workflows, backend services, data access layers, evaluation, observability, and reusable GenAI infrastructure used across product teams. You will not be focused solely on model research or prompt design. Instead, you will be a strong software engineer who can design, build, ship, and operate reliable AI-powered systems in production.
A Day In Your Life :
Build reusable infrastructure, SDKs, and internal frameworks for AI-powered product capabilities.
Design and implement AI agents, RAG flows, tool-calling workflows, and LLM orchestration pipelines.
Build production-grade GenAI services, APIs, and backend infrastructure.
Integrate LLM workflows with internal microservices, data platforms, vector search, and event-driven systems.
Design secure data-access patterns that enforce authorization, tenant separation, and user-level scope.
Implement evaluation, tracing, monitoring, and quality-control mechanisms for GenAI systems.
Improve latency, reliability, fallback behavior, cost efficiency, and production readiness.
Work on customer-facing AI experiences, including conversational and proactive agentic product flows.
Collaborate with backend engineers, product managers, data engineers, AI/ML engineers, and domain experts.

We are seeking a Software Engineer to join Dashs core development team. You will design, build, and ship the platform that powers discovery, session-aware detection, policy governance, and runtime enforcement across workstations, SaaS, and cloud. You will work on scalable, low-latency services that process agent activity in real time and enforce security policies without slowing builders down. This role requires strong engineering fundamentals, a focus on system reliability, and an interest in the unique challenges of agentic security.
Responsibilities:
Design and Implement Services: Design, develop, and deploy scalable backend services and APIs for the Dash Security platform (customer and admin APIs, detection ingestion, aggregation, and control-plane services).
Build Core Features: Implement features for agent/MCP/skill discovery, session and intent-aware detection, policies, and runtime enforcement across coding agents and enterprise AI platforms.
Optimize Runtime Protection: Maintain and optimize high-throughput detection and enforcement pipelines that operate at enterprise scale (ingestion, detectors, verdicts, and policy dispatch).
Integrate with Platforms: Build and deepen integrations with coding agents, SaaS AI platforms, identity providers, EDR, SIEM, and outbound action systems to ingest telemetry and enforce controls.
Ensure Reliability: Focus on code quality, performance, monitoring, and stability through robust testing, CI/CD, and operational excellence.
Collaborate with Research: Partner with the AI Security Research team to turn findings, signatures, and heuristics into production-ready detectors and enforcement logic.
Contribute to Architecture: Participate in technical design and architectural reviews across our codebases, agents, and event-driven backend services.
Stay Current: Continuously learn and apply new technologies, development methodologies, and security best practices.

As a Senior Backend Engineer, you will play a key role in building and evolving core backend systems.

Youll work on high-scale, cloud-native services that power critical business flows, with end-to-end ownership - from design and architecture to production, monitoring, and continuous improvement.

Youll collaborate closely with engineers, product managers, and other stakeholders, and serve as a technical leader within the team.



Responsibilities

Design, build, and maintain scalable, high-availability backend services in a cloud-native environment
Take end-to-end ownership of features: design, implementation, deployment, monitoring, and ongoing optimization
Contribute to system architecture, API design, data modeling, and event-driven flows
Write clean, high-quality, and maintainable code, and participate in design and code reviews
Optimize performance, reliability, and resource usage (databases, infrastructure, integrations)
Collaborate with Product and other stakeholders to translate business requirements into technical solutions
Mentor and support other engineers, contributing to a strong engineering culture and best practices
Continuously improve engineering standards, tooling, and workflows as the company scales

We are looking for an experienced and hands-on Automation Tech Lead to lead the technical direction of our automation infrastructure and drive the adoption of scalable, reliable, and maintainable automation solutions.
The role combines hands-on engineering, technical leadership, architecture, and mentoring, working closely with QA, R&D, DevOps, and Product teams.
What you'll do:
Define and drive the technical strategy and architecture of automation.
Design, develop, and maintain scalable automation frameworks.
Develop automated tests using Python and pytest.
Integrate and maintain automation within CI/CD pipelines, including Jenkins.
Define automation best practices, coding standards, and quality guidelines.
Improve automation stability, execution time, coverage, and maintainability.
Lead debugging and root-cause analysis of complex automation and system issues.
Mentor automation engineers and conduct code reviews.
Collaborate with R&D to improve product testability and quality.
Evaluate and introduce new technologies and approaches, including AI-based testing and automation.