דרושים » תוכנה » Staff engineer - AI Builder

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

We are looking for a Staff Engineer.
What Youll Do:
Lead architecture and system design for critical components of the Developer Experience platform, ensuring scalability, resilience, and long-term maintainability.
Own end-to-end delivery of complex initiatives, from requirements gathering and design to implementation, rollout, and observability.
Design, implement, and maintain robust microservices supporting high-throughput and low-latency operations.
Define and uphold API design standards, including gateway configuration, versioning strategy, and long-term lifecycle management.
Build and optimize backend systems that enable developer-facing products such as SDKs, APIs, and webhooks.
Work with both relational and NoSQL databases to ensure data consistency, scalability, and performance.
Collaborate with cross-functional teams to design systems that meet operational and business requirements.
Research and implement cloud-native architectures to support growth and scalability.
Contribute to the creation of developer tools and standards that improve the usability of our APIs and SDKs.

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.

we are seeking a Principal Software Engineer to join the Architecture team within Cortex XSOAR. You will play a pivotal role in building scalable agentic AI infrastructure, driving the next evolution of cybersecurity automation. This role is based predominantly in our Tel Aviv office and is ideal for innovators who thrive on disruption, collaboration, rapid self-learning, and leadership.
In this role, you will design and implement high-performance, distributed backend services, integrating advanced AI capabilities to enhance proactive threat detection and mitigation. Youll work closely with AI experts, security researchers, and software engineers to develop cutting-edge autonomous security agents.
While prior production experience with AI is not mandatory, a background in LLMs, AI-driven automation, or intelligent agents is highly advantageous. Cloud-native development experience is required.
More information about XSOAR, here.
Your Impact
Architect and develop scalable backend services that power agentic AI capabilities within Cortex XSOAR
Integrate AI-driven automation into security workflows, leveraging LLMs and autonomous agents
Design and optimize cloud-native systems for high performance, resilience, and security
Collaborate across multidisciplinary teams to drive AI adoption within our product suite
Lead architectural decisions and conduct rigorous code/design reviews to uphold technical excellence
Continuously optimize system performance, scalability, and fault tolerance in high-stakes environments
Mentor engineers, fostering technical excellence across the team.

Were looking for a Product Manager to lead LLM Infrastructure - a foundational role driving the development of systems that enable smarter, AI-powered decision making across the marketplace.

As the PM for LLM Infrastructure, youll shape the capabilities that turn unstructured data into structured, explainable, and actionable insights. Youll work closely with ML engineers, data scientists, and product leaders to design scalable tools and frameworks that support use cases across personalization, matching, search understanding, trust and safety, and more.

Your mission will be to build reliable and extensible LLM-based systems that serve as core building blocks for future-facing product innovation.

What am I going to do?
Define the product vision and roadmap for LLM infrastructure, aligning with long-term company strategy and cross-team needs.
Lead the development of scalable systems that extract meaning.
Structure from conversational and behavioral data.
Drive adoption of LLM capabilities across by building unified APIs, shared frameworks, and streamlined integration pipelines.
Partner with engineering, data science, and research teams to deliver high-quality infrastructure that powers AI-native product experiences.
Collaborate on system design and architecture decisions to ensure alignment between technical solutions and product scope.
Ensure reliability, scalability, explainability, and performance in all LLM-based systems.
Manage technical complexity and connect infrastructure efforts with clear business value.

We are seeking a talented Software Architect. This is a unique opportunity to work with US clients and engage in global projects, leveraging your extensive skills in generative AI tools.
As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative projects.
Key Responsibilities:
Advanced Backend Development: Lead the development of scalable, secure, and maintainable backend systems using Python and frameworks like FastAPI.
System Design & Architecture: Architect robust backend solutions and design efficient RESTful APIs with asynchronous programming support.
Core Technical Strengths: Utilize deep knowledge of Object-Oriented Programming (OOP), asynchronous design patterns, and software engineering best practices.
DevOps & Containerization: Implement Docker for containerizing applications and Kubernetes for orchestrating microservices-based deployments in scalable, production-grade environments. Manage CI/CD pipelines and deployment automation.
Database Expertise: Design schemas, optimize queries, and manage data consistency across distributed systems using PostgreSQL and CosmosDB.
Quality Engineering & Testing: Write comprehensive unit tests, enforce code quality through peer reviews, and integrate test automation in CI workflows.
Technical Mentorship & Team Collaboration: Mentor junior developers, drive code quality, scalable design, and agile delivery. Collaborate effectively across DevOps, frontend, and product teams.
Agile Development & Ownership: Participate in sprint planning, backlog management, and stakeholder communication. Take full ownership of modules, ensuring timely and reliable delivery in Agile/Scrum environments.
Exposure to Agentic Flows: Leverage experience with agentic flows to enhance system performance and reliability.

We are looking for an experienced AI leader to lead our AI & ML engineering efforts, as part of the core infrastructure of the company. AI/ML are core components of Navina unique technology, and a significant part of our technical edge. This is a unique opportunity to take a leadership role in building the tools and infrastructure that power the models driving Navinas success.

Youll directly lead a team of ML engineers in designing scalable production systems, collaborating with cross-functional stakeholders, and mentoring team members as we scale our ML platform and capabilities. In addition - you will lead the AI-first approach of the company, evangelizing AI coding and development practices, providing thought-leadership on AI across the company inside the engineering team and across the broader company.

Responsibilities
Provide technical leadership and team management for the Machine Learning Engineering team, including mentoring team members, and encourage ongoing personal and professional growth.
Define and drive the roadmap for AI & ML infrastructure in collaboration with other technical leaders and data science team, ensuring alignment with broader engineering and organizational goals.
Remain actively involved in the architecture and development of systems that enable scalable and reliable model training, deployment, serving, and monitoring.
Be the go-to person for AI development across the company. Guide and mentor others to AI-first development tools, methodologies, and ways of thinking about problems we are solving.
Work closely with data science, product, medical, and dev teams to understand evolving needs and deliver infrastructure and tooling that improve development velocity and model reliability.
Continuously learn , try and help productize AI and ML technologies to drive the overall engineering efficiency higher.

We are looking for an experienced MLE Team Lead to lead our Machine Learning Engineering team as part of the Infrastructure group. AI/ML are core components of Navina unique technology, and a significant part of our technical edge. This is a unique opportunity to take a leadership role in building the infrastructure that powers the models driving Navinas products.

Youll lead a team of ML engineers in designing scalable production systems, collaborating with cross-functional stakeholders, and mentoring team members as we scale our ML platform and capabilities.

Responsibilities:
Provide technical leadership and team management for the Machine Learning Engineering team, including mentoring team members, and encourage ongoing personal and professional growth.
Define and drive the roadmap for ML infrastructure in collaboration with other technical leaders and data science team, ensuring alignment with broader engineering and organizational goals.
Remain actively involved in the architecture and development of systems that enable scalable and reliable model training, deployment, serving, and monitoring.
Own the engineering aspects of the ML lifecycle, including the design of efficient production-grade deployment mechanisms, robust observability and maintenance practices.
Work closely with data science, product, medical, and dev teams to understand evolving needs and deliver infrastructure and tooling that improve development velocity and model reliability.
Continuously evaluate emerging tools and best practices in ML infrastructure and thoughtfully integrate relevant technologies to strengthen the teams capabilities.

As a Principal DevOps Engineer in our Platform Engineering team, you will lead the design and implementation of cutting-edge CI/CD pipelines and cloud architecture that powers our development environment. You'll drive initiatives to enhance developer productivity through automation, tooling, and infrastructure improvements, working with a modern tech stack including Kubernetes, Python, cloud-native and high-scale technologies.
Your Impact
Architect and implement scalable, resilient CI/CD pipelines and cloud infrastructure that supports our engineering organization's evolving needs
Design and develop internal developer tools and platforms that significantly improve developer experience and productivity
Drive the evolution of our Kubernetes-based deployment infrastructure in Google Cloud Platform, ensuring security, reliability and performance
Optimize and scale our CI/CD infrastructure including Jenkins, GitLab, TeamCity, and artifact management systems
Mentor and guide other engineers on DevOps best practices, infrastructure design, and implementation strategies
Drive adoption of infrastructure-as-code, automated testing, and deployment methodologies
Collaborate with development teams to understand their needs and implement solutions that accelerate their workflow
Establish standards and best practices for infrastructure reliability, observability, and performance.