דרושים » תוכנה » Software Engineer - AI Tools & Innovation

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

As part of our ongoing innovation, were expanding our capabilities around AI-driven development and automation. The Dev AI Infra & Tools team leads this transformation - building the internal platforms and tools that empower our engineers to design, test, and deliver faster, smarter, and more securely.

Youll work hands-on with Generative AI frameworks and agents, developing the systems and integrations that change the way our engineering teams work.



Key Responsibilities
Design and build AI-driven internal tools that enhance developer productivity.
Develop and maintain the infrastructure supporting GenAI agents and automation frameworks.
Prototype and experiment rapidly, turning ideas into practical solutions.
Collaborate with DevOps, backend, and product engineers to identify and implement high-impact GenAI use cases.
Evaluate new Generative AI and agent-based technologies and integrate the most promising ones into production.
Define and track efficiency metrics to continuously improve developer velocity and experience.

Required Software Engineer - Al Platform
About Us
We help modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, weve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over ~4500 midsize and multinational companies and over 1 Milion users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
What this role is really about
Were building our internal AI Platform as a foundation that enables safe, scalable, and cost‑effective AI across the company. Our mission is to support internal business units in becoming more productive and driving business growth. As a Software Engineer on Business Innovation (Internal), youll develop high‑leverage platform capabilities used by Product, Customer Success, Sales, Operations, Data, and IT. Youll work across the entire stack, from APIs and services to data and UI. transforming business requi
Build core AI platform services - Design and implement agent orchestration, prompt management, RAG, Connectors, and evaluation pipelines that power AI experiences across the company.
Develop complex agentic workflows - Develop a multi-step workflow that coordinates tools and services with proper observability, guardrails, and cost controls (using OpenAI Agent SDK, LangGraph, or a similar framework).
Build LLM evaluation and optimization systems -Develop evaluation harnesses, offline/online experiments, prompt-testing frameworks, and dashboards to balance quality, latency, and spend across all AI services.
Ship the internal AI portal - Build user-facing products that democratize AI access: prompt directories, agent designers, templates, approval workflows, and more.
Ensure security and compliance - Develop RBAC, data classification, PII redaction, audit logging, and policy enforcement.
Create robust integrations - Connect the platform with Salesforce, NetSuite, Slack, Snowflake, HRIS, and other critical business systems.
Establish operational excellence - Implement CI/CD, testing strategies, monitoring/tracing, and SLOs for high-reliability services.
Enable developers - build SDKs, CLIs, and templates that help teams create safe, scalable AI workflows. Lead technical discussions and write design documentation.

Our group is building an ambitious, AI-powered product at the heart of Check Points strategic vision - combining cutting-edge AI technologies with world-class cybersecurity expertise. This role offers a unique blend of deep technical challenges, hands-on development, and meaningful product impact. Youll have access to some of the best cybersecurity data sources available, working in a fast-paced, innovation-driven environment that combines the agility of a startup with the stability of a global leader.

If you're passionate about building state-of-the-art systems, solving complex engineering problems, and working with a great team to deliver real impact - wed love to hear from you.

Key Responsibilities
Design, architect, and implement a complex AI-powered security product
Develop and optimize scalable, reliable, and high-performance data pipelines, APIs, and cloud services
Integrate AI models and in-house agents into robust production systems
Collaborate closely with cross-functional teams, including data scientists, software engineers, and product teams, to drive innovation from concept to deployment

We are seeking a highly skilled Senior Networking AI Platform Engineer to join our Applied Networking AI group. In this role, you will help design and develop cutting-edge AI solutions, integrating them seamlessly into a variety of products. Youll collaborate closely with multi-functional teams of data scientists, software engineers, and DevOps professionals to ensure the efficient deployment, monitoring, and optimization of machine learning (ML) models.
As a key contributor, you will drive the entire software development lifecycle-from conceptualization and architecture to implementation and production-while working closely with engineering teams to solve complex problems and help build a successful company practice.
What you'll be doing:
Lead the design, development, and deployment of robust software systems across different platforms and environments
Architect, design, and implement scalable and high-performance software solutions, handling complex requirements and integrating various subsystems
Ensure systems are maintainable, flexible, and well-documented, with an emphasis on performance and security
Adapt to new tools, technologies, and frameworks, and be capable of taking ownership of the development process from conception to deployment
Supply innovative ideas and solutions, driving continuous improvement in both code quality and system efficiency
Develop and maintain scalable infrastructure for handling and deploying security and networking ML models in production, ensuring high availability, scalability, performance.
Design and implement data pipelines to efficiently process and transform large volumes of data for training and inference purposes.
Optimize and fine-tune ML models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.
Collaborate with data scientists and software engineers to operationalize and deploy ML models, including model versioning, packaging, and integration with existing systems.

As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our companys next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code models-optimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

Were looking for a versatile, talented, and highly motivated Data Engineer to join our growing team.

If youre passionate about solving complex problems, thrive in dynamic environments, and love working at the intersection of data engineering, machine learning infrastructure, and AI innovation, this role is for you.

As a Data Engineer, youll play a key role in shaping how data flows through the company, from building scalable pipelines and robust infrastructure to powering data science models and enabling internal teams with intelligent GenAI-powered tools. This is a hands-on, high-impact role with plenty of room for ownership, creativity, and growth.

This is a high-impact role where your work will shape how the company leverages data and AI. If you want to build, innovate, and push boundaries in a collaborative and fast-moving environment, wed love to meet you.

Responsibilities
Own the entire data lifecycle from understanding business needs and building reliable pipelines to ensuring data quality, observability, and performance.
Design, build, and scale modern data infrastructure including data lakes, warehouses, and complex ETL/ELT pipelines.
Integrate and consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a single, trusted source of truth.
Implement and manage CI/CD, observability, and infrastructure-as-code in a cloud-native environment.
Work with the data science team on their ML pipelines, giving data scientists the infrastructure and automation they need to deploy models to production with speed and confidence.
Collaborate with cross-functional teams to embed GenAI agents into business processes, creating smart workflows that boost efficiency and reduce manual work.
Develop frameworks and internal tooling that empower other teams to safely adopt AI and accelerate innovation.
Optimize data infrastructure for performance and cost-efficiency, with a focus on BigQuery optimization.
Ensure high data quality and integrity across large-scale ETL processes. Work closely with analysts, data scientists, and product managers to support data modeling, governance, and analytical initiatives.

Our Networking Research group is seeking a forward-thinking Engineering Manager with a product leadership approach to manage a team of Software Engineers, AI Agent Developers, and Researchers.

In this role, you will bridge the gap between brand-new AI research and practical engineering. You will lead the charge in integrating autonomous AI agents into the daily workflows of our architects, hardware designers, and researchers. You will be responsible for understanding internal engineering bottlenecks, researching the latest academic and industry advancements, and translating them into deployed production tools using our AI stack.

What you'll be doing:

Team Leadership & Strategy: Lead and mentor a mixed team of SW engineers and researchers, balancing the agility of research with the responsibility of production software engineering.

Product Engineering: Partner with internal engineering teams (Hardware, Architecture, Research) to analyze their workflows, identify friction points, and architect Agentic AI solutions to accelerate their work.

Applied Research: Actively monitor the latest AI trends, academic papers, and technical blogs (LLMs, Agents, RAG). Translate these insights into concrete features and tools for the team.

Agent Architecture: Be responsible for the design of scalable frameworks for AI agent interaction, ensuring they can reason, plan, and orchestrate tasks within complex engineering environments.

SW-Focused MLOps: Define and implement the software lifecycle for AI models - from fine-tuning to deployment - utilizing our AI deployment tools and ensuring seamless CI/CD.

Production Deployment: Ensure reliable operation of agent fleets, optimizing for latency and resource consumption while maintaining security and access controls.

We are looking for a Full Stack Developer.
our developers take full ownership across the stack from ideation and architecture to deployment, observability, and maintenance.
Youll craft seamless user experiences, build scalable backend systems, and help shape how AI integrates into our engineering workflows and product development.
In our full CI/CD environment, youll work closely with a passionate team, leveraging modern technologies and AI-driven tooling to accelerate development, automate repetitive tasks, and deliver high-quality, high-impact solutions that empower millions of small businesses worldwide.
Key Responsibilities:
Collaborate with product managers, designers, and fellow engineers to bring ideas to life.
Build next-generation web applications focused on user experience and scale.
Create efficient and reusable front-end abstractions and systems, while adopting AI-powered tools that accelerate UI development (e.g., Figma-to-code generation).
Craft secure, scalable, and maintainable backend services, and contribute to decisions around how AI/MCP capabilities are exposed across microservices.
Lead architecture design, implementation, and monitoring of solutions.
Perform code reviews, drive engineering best practices, and help the team adopt AI tools that boost productivity and improve developer experience.
Champion modern technologies including AI integrations, MCP patterns, observability, and automation to push our engineering organization forward.

we are looking for a Senior Data Scientist.
As an Applied Researcher, you will play a central role in advancing our AI capabilities -fine-tuning and optimizing large language models to extract legal insights and power intelligent decision-making at scale. Youll explore new model architectures, training paradigms, and evaluation methods to push research from experimentation to impactful, production-ready innovation.
Youll collaborate closely with data scientists, engineers, and domain experts to design and validate research prototypes, integrating cutting-edge methods such as model distillation, retrieval-augmented generation (RAG), and knowledge-graphbased reasoning.
Responsibilities:
Design and evaluate new model architectures, training objectives, and loss functions that enhance generalization and domain adaptation.
Research and innovate in areas such as model compression, knowledge distillation, and retrieval-augmented generation (RAG) to improve inference efficiency and interpretability.
Publish and present innovative findings internally and externally to advance the organizations leadership in applied AI research.
Collaborate cross-functionally with engineering, product, and data science teams to transition research prototypes into scalable production systems
Drive measurable impact by translating research innovations into deployable solutions that improve model performance, scalability, and user outcomes.
Contribute to the research community through publications, open-source contributions, or collaborations, showcasing thought leadership in LLM fine-tuning and applied AI innovation.