לוח משרות דרושים AI Engineer משרה מלאה, לחיפוש זה נמצאו 138 משרות

A senior individual-contributor role reporting to the VP of MIS (CFO Office).




Key Responsibilities
The role spans two connected layers, and youll move fluidly between them:

The platform. Build and maintain the shared integration and automation infrastructure layer that connects our internal systems and exposes them to AI safely - reusable connectors, reliability, security, and observability.

The solutions. Build internal tools, automations, and AI agents on top of it - integrations across enterprise SaaS (Salesforce, NetSuite, Slack, Okta), and LLM-powered workflows for things like triage, provisioning, document processing, and reporting.

The right tool for the job. Low-code/iPaaS, custom code, or a hybrid - whatever delivers value fastest and stays maintainable, with responsible-AI practices throughout.

How Youll Work
Deliver MVP-first and iterate on real usage; favor pragmatic, simplicity-first solutions over over-engineering

Own what you build end to end - design through production support - with documentation others can maintain

Communicate trade-offs clearly, and quantify the value you deliver

Scope
In scope: the internal AI-integration and automation platform and everything built on it; business infrastructure for teams across Finance, HR, GTM, Security, and IT; integration reliability and observability.

Out of scope: physical IT operations (device provisioning, inventory, AV) and endpoint/office IT support.

We're looking for a Senior AI Solutions Builder to join our Product team. In this role, you will design, build, and ship AI-powered solutions that enhance productivity and drive measurable business value across the organization.

You will operate at the intersection of AI, data, pricing and business - owning the end-to-end development of agents, copilots, and workflow automations that directly inform decisions and eliminate manual work.

You are both a builder and an enabler. You ship solutions yourself and raise the AI capability floor for the teams around you. You'll collaborate closely with Product, Engineering, CS, Sales, and builders across the company to deliver outcomes that improve decision velocity, product and operational efficiency, and long-term growth.

You Will
Design and ship AI-powered copilots, agents, and decision-support tools for the Product team, starting with Pricing

Build data pipelines and analytical models for pricing intelligence

Develop autonomous agents that automate recurring Product tasks

Automate manual workflows across product tools so the right action happens when a signal fires

Build LLM-based scoring models that give roadmap and prioritization decisions a data backbone

Enable and upskill product teams through AI playbooks, sessions, and hands-on co-building

Collaborate with builders across Engineering, CS, GTM, and other teams to co-create solutions that scale

Define and track impact: time-to-insight, decision velocity, manual hours eliminated, and business outcomes

We're a small, fast, high-ownership team, and we're looking for a Senior Backend Engineer to make work for agents - both by building new agent-facing infrastructure and by reshaping our existing platform for a world where the caller is a machine. Some of this is greenfield. Much of it is taking APIs, auth, and SDKs and making them ergonomic, legible, and reliable for agents.

Its a problem the whole industry is still figuring out. Youll help define what great API design looks like when the caller is not a human developer, but an agent acting on their behalf.

What you'll do
Build the surfaces agents call directly: API-first account provisioning, machine-to-machine authentication, scoped credentials, and agent-level identity and attribution.
Own our MCP (Model Context Protocol) servers and an agent-first CLI - let coding agents and LLMs discover and invoke reliably, engineered for agentic callers: token-efficient tool schemas, machine-parseable output, and loud, actionable failures instead of silent ones.
Harden the agent media path - make upload and core media operations reliable for non-human callers, eliminating the ambiguity and silent-failure modes that cause agents to drop off mid-task.
Make agent behavior measurable - partner on the instrumentation, signals, and attribution that tell us whether agents are succeeding.
Work across a polyglot backend - Node.js/TypeScript for the agent tooling layer, with Ruby/Rails and Go in the core platform.
Ship, measure, iterate - prototype quickly, dogfood the experience, and represent the agent's perspective in every design decision. Work closely with Product, Ecosystem, and Discoverability across the AX team.

We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

We're looking for an AI Engineer who is equal parts builder, enabler, and visionary.
This is a rare opportunity to join a small, elite team at the ground floor and have outsized impact on how AI is designed, built, and shipped across a globally recognized cybersecurity platform.
If you thrive at the intersection of cutting-edge AI research and real-world production systems and you want your fingerprints on something that matters - read on.
Why Join Us?
Greenfield opportunity - you're not joining a mature team with fixed patterns, you're helping define them.
Real impact at scale - your work will influence products used by thousands of organizations worldwide.
A team of great people - small, senior, and genuinely collaborative.
Freedom to innovate - we encourage bold ideas, fast experiments, and honest feedback.
our company's AI moment - AI is a company-wide strategic priority, and this group is at the center of it.
*we are an equal opportunity employer committed to diversity and inclusion.
Key Responsibilities
What You'll Do:
Build AI infrastructure - Design and develop the foundational tools, frameworks, and pipelines that power the group's AI capabilities, with a focus on LLMs and Generative AI.
Enable AI across the team - Act as the group's AI enablement engine: establish best practices, create internal tooling, and uplift teammates to work effectively with AI systems.
Own AI agents & agentic workflows - Design, implement, and iterate on autonomous agents and multi-step AI pipelines integrated with a variety of tools and environments.
Bring AI to production - Take models and capabilities from prototype to production-grade systems - reliable, scalable, and observable.
Shape the big picture - Contribute to the group's AI strategy, not just its execution. We want someone who asks "why" before diving into "how."
Stay ahead of the curve - Continuously research and evaluate emerging AI techniques, models, and tools - and bring what's relevant back to the team.
Collaborate and communicate - Write clearly. Think clearly. Work closely with researchers, engineers, and product stakeholders to align on goals and drive outcomes.

The Architect leads the design and implementation of scalable AI platforms and central services for AI, creating shared capabilities, tools, and frameworks that transform how our company builds, delivers, and operates products.
Beyond architecture, this role drives strategic, high-impact projects with powerful ROI that positively disrupt operations and elevate customer outcomes, improving efficiency, innovation, and product value across the company.
Strategic Objectives:
Accelerate AI Transformation across the organization by designing and operationalizing central AI services and a unified platform framework that powers key transformation initiatives, including Agentic Workflows.
Institutionalize AI Engineering and Governance Standards through common architecture, services, and enablement frameworks ensuring scalability, security, quality, and compliance.
Deliver measurable transformation outcomes through strategic, ROI-driven projects that reshape how our companys products are built and operated, directly benefiting customers and business performance.
Drive sustainable transformation at scale, balancing rapid innovation with operational excellence and long-term maintainability.
Key Responsibilities
Architect the AI Transformation Framework
Design and own the end-to-end architecture that enables the companys AI Transformation vision - spanning data, models, pipelines, APIs, and governance layers.
Define blueprints and integration standards to embed AI and automation throughout the SDLC, from ideation to delivery.
Build Generative AI Platforms and Central Services
Lead the design and implementation of the AI Enablement Platform and central AI services powering transformation initiatives such as Agentic Workflows and the Knowledge Hub.
Create scalable, secure, and modular AI components that can be leveraged across product lines and engineering domains.
Partner with infrastructure, platform, and security teams to operationalize LLM-based services, retrieval systems, and agentic automation flows.
Drive Strategic Transformation Projects
Lead cross-functional initiatives that deliver tangible operational and business impact - improving speed, quality, and cost-efficiency across the product organization.
Develop strong business cases and ROI frameworks to prioritize and communicate transformation value at the executive level.
Translate successful outcomes into reusable playbooks and AI cookbooks that scale across teams, roles, and product domains.
Technical Leadership and Enablement
Act as the senior technical authority and coach for AI transformation initiatives, guiding teams through architecture reviews, proofs of concept, and scale-up phases.
Mentor internal architects and tech leads to develop AI-native architectural competencies.

Were looking for a Backend AI Engineer to own and build our companys agentic AI architecture. This role sits at the intersection of backend engineering and production-grade AI systems. Youll design, build, and scale the backend that powers our AI creators, enabling intelligent, reliable, and observable agentic workflows at scale.
Youll work on orchestrating multi-step AI workflows that involve LLMs, tools, and decision logic, and ensure they operate reliably under high load and real-world usage. A key part of the role is designing systems that can handle non-deterministic AI behavior, recover gracefully from failures, and continue to perform as usage and complexity grow. Youll also be responsible for making architectural decisions that support scalability, low latency, and long-term maintainability of our AI platform.

Are you an AI Analyst ready to translate raw model output into a reliable, high-quality production system? Do you excel at the craft of Prompt Engineering and thrive on the challenge of ensuring Generative AI output meets rigorous quality standards in mission-critical applications? Join our R&D Operations Team. You will be the AI analyst responsible for the end-to-end quality, performance, and operational tuning of our Generative AI-driven support system (Co-Pilot). Your mission is to actively shape the model's intelligence, govern the data it uses, and implement the mechanisms that guarantee its accuracy, directly accelerating our customer support engineering velocity.
Key Responsibilities
Support & Customer Advocacy: Champion the Support Journey in Engineering. Develop in-product support instructions that reflect and address real incoming cases, enhancing the quality and effectiveness of AI feature solutions.
Model Quality Validation: Use existing evaluation platforms and methodologies to validate production models. Monitor quality metrics to continuously assess and rank AI answers for accuracy and reliability.
Prompt Engineering & CT Loop: Drive the Continuous Training loop through systematic prompt engineering (refining and versioning inputs). Analyze failures to define R&D actions or features needed to close model performance gaps.
AI Knowledge Governance: Act as AI Content Governor, implementing controls to verify and ingest compliant knowledge base content, ensuring a quality data source.
Cross-Functional SME: Serve as the AI Support Co-pilot Subject Matter Expert, partnering with R&D and Support Enablement to translate quality issues into core model logic improvements and feature development.

As a Senior AI Software Engineer on our Generative AI foundation team, you will build AI agents and shared infrastructure that power GenAI capabilities across the company. You will be involved in the full software lifecycle, from fast-moving prototypes to production-grade systems, enabling our companys product lines to adopt agentic workflows safely and at scale. You will collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence.
Your Impact:
Engage in the full software lifecycle, from fast-moving prototypes and POCs to production-grade, observable systems.
Collaborate with product managers, researchers, and engineers to translate ideas into robust services.
Work hands-on with leading LLMs and the modern agentic ecosystem, leveraging a wide range of AWS services.
Use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve solutions.
Implement solid design, flexible implementation, strong telemetry, and production feedback loops.

We are seeking an experienced and visionary ML Engineer to join our dynamic technology organization. The successful candidate will be a part of a team of talented AI Engineers, Building agentic AI solutions, driving innovation and delivering business value through advanced Generative AI solutions & machine learning techniques. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge Gen AI and LLM methodologies and a passion for continuous learning and development.

Responsibilities
Build the solution: Own end-to-end technical delivery of agentic systems, from source-system integration through agent design, development, evaluation, and production deployment.
Integrate AI systems with our source systems (Salesforce, Databricks, Splunk, internal APIs, business applications). Handle agent harness and orchestration.
Handle the operational handover to the business function and any necessary support transition.
Collaborate across teams: Partner closely with data engineering, platform, security, and business teams to align on requirements, dependencies, and integration points.
Engage stakeholders: Gather requirements directly from business functions, communicate technical trade-offs clearly, and keep stakeholders informed on progress, risks, and timelines.
Uphold quality and reliability: Establish and maintain best practices for code quality, testing, evaluation, monitoring, and observability of deployed AI systems.
Contribute to the team's technical growth through knowledge-sharing and help shape engineering standards and reusable patterns.
Stay current: Continuously evaluate emerging Gen AI, LLM, and agentic frameworks, and recommend tools and approaches that improve delivery speed and solution quality.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

we are looking for a AI Adoption Engineer.
Responsibilities:
1. Use Case Discovery & Prioritization
Embed with non-R&D teams (CS, Sales, Marketing, Finance, HR, Operations) to understand workflows and identify where AI creates the highest leverage.
Define and prioritize whats worth building, maintaining a live backlog aligned with VP of AI.
Good discovery is the difference between automation that gets used and automation that gets ignored.
2. AI Tool Development & Delivery (~40%)
Build custom tools, workflow automations, Cowork skills, and AI integrations with existing business systems.
Validate with real users, iterate on adoption signals, and transition stable tools to team ownership.
This role leads by shipping. Working tools - not proposals - are the primary output.
3. Enablement & Adoption
Ensure tools get used: onboarding sessions, playbooks, and hands-on support through behavior change.
Build team confidence and self-sufficiency over time; avoid creating dependency on a single person.
4. AI Landscape Awareness
Evaluate new models, tools, and capabilities for internal relevance and bring what matters back to Navina.
Collaborate with VP of AI to maintain a current roadmap for internal AI operations.

we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

The Prisma Browser group is building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
Prisma Browser is an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.

Responsibilities
Take full end-to-end ownership of features - from product thinking and design through development, testing, deployment, and post-production monitoring.
Collaborate with cross-functional teams to design, develop, and deploy high-quality web applications and services.
Champion and apply agentic development practices, leveraging AI-assisted tooling and automation to accelerate R&D velocity.
Develop robust and scalable systems using Node.js,C#,React, TypeScript and related frameworks.
Own the full DevOps lifecycle - CI/CD pipelines, containerization, release management, and production observability.
Optimize web applications for performance, scalability, and security across both microservice and monolithic architectures.
Write and maintain automated tests (unit, integration, end-to-end) to ensure code quality and reliability.
Utilize version control systems, particularly Git, for code management and collaboration.
Stay current with emerging technologies, AI tooling, and modern engineering trend.