לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 168 משרות

Palo Alto Networks is seeking a Senior or Principal Backend Engineer (we are open to hire both levels) for our Cortex engineering group, focusing on Cortex XSOAR, Cortex XSIAM, and new Cortex AI solutions. In this role, you will design and implement robust backend services for our leading-edge security orchestration, automation, and response platform. You will also contribute to creating innovative AI-based solutions, enhancing shared Cortex infrastructures. This is an exceptional opportunity for those eager to advance Cortex products with AI-driven capabilities and make a significant impact in the cybersecurity industry.
Your Impact:
Own the end-to-end backend development of features and components, from design and development to testing, deployment, and maintenance.
Proactively collaborate and exchange information with peers across different teams and disciplines to shape solutions and ensure alignment on product integrations.
Contribute to team-wide efforts including code reviews, design reviews, and architectural decisions, ensuring high-quality and maintainable code.
Apply a production-oriented approach, providing real-time mitigation and effective solutions to production issues to ensure platform stability and reliability.
Challenge curiously and positively by exploring new technologies and methodologies to enhance our backend services and AI capabilities.

Required Principal AI Software Engineer (CORA AI)
Your Career:
As a Principal 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 CyberArks 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 looking for a highly motivated AI Research Student for our Robotics & Simulation AI team. You will be passionate about data science, AI quality measurement, and the intersection of AI with high-accuracy industrial domains. This role is ideal for someone who grows with challenging existing assumptions, defining rigorous evaluation methodologies, and pushing AI systems toward measurable reliability. You will combine strong data science and research skills with hands-on experimentation in a production AI product that controls robotic manufacturing simulations.

Key Responsibilities

AI Quality & Stability Research

Define and implement metrics to measure the stability, accuracy, and reliability of our production AI Copilot (PSCoPilot)
Design evaluation frameworks for AI agents operating in safety-critical robotics and simulation environments
Build observability and tracing pipelines using platforms like Langfuse to monitor Copilot performance, token usage, latency, and tool-calling success rates
Analyze failure modes, hallucination patterns, and tool-calling accuracy across 48+ MCP-exposed robotic operations
Develop automated regression and benchmark pipelines to track Copilot quality over time

Data Science & Experimentation

Conduct statistical analysis on Copilot interactions (tool selection accuracy, collision detection correctness, path planning success rates)
Research and apply techniques from AI evaluation literature (LLM-as-judge, human-in-the-loop validation, domain-specific benchmarks)
Leverage LangChain and similar orchestration frameworks to prototype evaluation chains, structured agent workflows, and comparison experiments
Explore how multi-layer agent architectures (fast triage + deep execution) affect accuracy and cost trade-offs
Challenge the team with data-driven insights on where the Copilot underperforms and why

Domain AI Research

Investigate how to improve AI reasoning for robotics tasks requiring high precision (welding, clearance checking, reachability analysis)
Research grounding techniques that reduce errors in domains with zero tolerance for incorrect outputs
Explore and apply new AI technologies (GenAI tools, AI coding assistants, agents, MCP-based solutions) to enhance Copilot capabilities
Validate technical feasibility through hands-on experimentation with our production MCP bridge and two-layer streaming agent engine

Communication & Documentation

Document findings, benchmarks, and technical recommendations
Present results to technical and business partners
Collaborate with the team to translate research insights into production improvements

The Senior Engineer will drive end-to-end AI projects, architect reliable AI platforms, and collaborate closely with product, engineering, and business teams to deliver high-impact solutions.



Summary of Key Responsibilities

Lead the design and implementation of Gen AI platform components using Python and modern microservices.
Drive engineering and operational best practices across AI projects.
Collaborate with technical, product, and business teams to deliver customer value and define product vision.
Lead end-to-end development of AI systems, including research, experimentation, deployment, and scaling.
Mentor and support engineers, fostering collaboration, knowledge-sharing, and continuous learning.
Analyze complex problems, define requirements, and propose AI-driven solutions.
Apply DevOps principles to maintain secure, scalable, and high-performance AI systems.
Design and implement secure APIs for safe interaction with AI models.
Stay up-to-date with the latest Gen AI technologies and trends, and bring innovation to the team.

We are seeking a highly skilled and motivated Senior Software Engineer GenAI to join our growing R&D team. In this role, you'll design, develop, and scale our next-generation backend platform, AI-driven workflows, and GenAI applications. You'll work with modern cloud technologies and LLMs to build resilient, high-performance systems while contributing to architecture, technical leadership, and mentoring.

This role is ideal for an experienced backend engineer who enjoys solving complex technical challenges, building scalable systems, and working with cutting-edge AI technologies.

Key Responsibilities

Design and develop scalable backend services using Python.
Build resilient distributed systems, microservices, and AI-driven workflows.
Integrate Large Language Models (LLMs) using AWS Bedrock and other AWS services.
Design and implement event-driven architectures and modern APIs.
Optimize databases, search capabilities, and caching strategies to support high-performance applications.
Contribute to cloud infrastructure, CI/CD pipelines, and observability practices.
Collaborate with Product, Data Science, and Engineering teams to deliver scalable solutions.
Provide technical leadership through architecture discussions, mentoring, and hands-on development.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

As a Product Manager at Balance, you will own and evolve core product experiences that power how businesses manage and optimize their financial workflows. You will lead cross-functional initiatives across engineering, design, sales, and customer teams to deliver scalable, reliable, and intuitive solutions. As part of our evolution, you will help shape AI- and agent-driven workflows that redefine how financial operations are built and experienced. You will drive product initiatives end-to-end, identify new opportunities for growth, and ensure alignment with business goals and regulatory requirements.

Responsibilities
Own a core product domain, driving strategy, execution, and outcomes.
Collaborate with cross-functional teams including engineering, design, sales, and marketing to define requirements and deliver high-impact solutions.
Work closely with internal stakeholders and external partners to understand APIs, integrations, and system constraints.
Engage directly with customers and prospects to understand their workflows, validate solutions, and support enterprise conversations.
Translate complex business processes into simple, scalable, and user-friendly product experiences.
Define and ship AI-powered and agent-based product capabilities, both in customer-facing workflows and internal tooling.
Continuously monitor and improve product performance across both technical reliability and key business metrics.
Stay informed about industry trends, regulatory changes, and emerging technologies to identify new opportunities.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Required Staff AI Support Engineer (AgentiX Support - Cortex)
Your Career
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.
Your Impact:
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.

we are looking for a AI Researcher.
As an AI researcher, you'll be at the forefront of researching advanced frontier model capabilities and agent behavior, and help shape the future of AI security evaluation and mitigation. In this role, you will advance the frontier knowledge of AI and agentic frameworks, methods of assessing their ability, and mitigations for dangerous capabilities.
Representative projects:
Researching capability elicitation methods to enhance model performance in evaluations.
Researching methodologies to assess generalization and coverage in model capabilities evaluation frameworks.
Contributing to academic publications and delivering research findings to customers.
Creating unique solutions to mitigate scenarios of AI loss of control or misalignment.
Advising and supporting the development of the products were building.

Join research team to develop the next generation of multimodal video diffusion models and bring cutting-edge research into real-time products used at global scale.
About the Team:
Our research team is small, fast-moving, and highly impactful. We develop multimodal generative models for real-time video creation, turning cutting-edge research into scalable products.
We are looking for researchers with deep expertise in generative video to join a team at the core of technology and help shape the future of generative AI.
Why Work ?
Work on cutting-edge video-generation technology at the forefront of AI.
See your research become part of products used at global scale.
Own meaningful research and engineering challenges as part of a small, high-impact team.
Help solve complex problems in real-time video generation.
Build technology that brings the next generation of AI assistants to life.

Morning is looking for a Senior Software Engineer with a builder mindset and a strong backend orientation — someone who enjoys taking ideas from concept to production, working across different parts of the stack, and doing whatever it takes to build great products. At Morning, engineers go beyond traditional role boundaries, taking ownership of solutions end to end rather than handing work off between specialized teams. We value people who are comfortable figuring things out, learning new technologies, and using AI tools to expand what they can build. You'll join our Delivery team, working on both existing products and new features. What you'll do
* Build and ship new features and improve existing products, taking ideas from initial problem-solving through to production.
* Work across the stack and beyond traditional engineering boundaries, taking a hands-on approach to solving problems and delivering complete solutions.
* Use AI-powered development tools extensively to explore solutions, write and improve code, debug issues, and accelerate development.
* Take ownership of the quality and reliability of what you build, critically evaluating AI-generated code and validating solutions before shipping.
* Explore new technologies and approaches to find better ways to build and deliver products. Why join Morning? Our customers rely on us to manage their financial data, so quality, reliability, and trust matter. We believe great engineers shouldn't be limited by rigid role boundaries. Our team takes a hands-on, end-to-end approach to building products — combining engineering, AI tools, experimentation, and whatever skills are needed to turn ideas into reality. You'll have room to take ownership, experiment, and make a meaningful impact, with the opportunity to see your work reach customers without long development cycles.

Advantages:

* Experience working with Databricks or Spark.
* Experience in fintech or other regulated environments.

Job responsibilities
Design, build, and maintain backend infrastructure and microservices supporting AI-driven features.
Collaborate closely with the infra and data groups to ensure smooth integration of AI models and services into Bobs core systems.
Develop and optimize APIs, data pipelines, and background processing workflows.
Ensure performance, scalability, and resilience of production systems handling real-time AI interactions.
Drive engineering excellence through code reviews, architecture discussions, and automation.
Mentor other backend developers and promote best practices in software design, testing, and deployment.

We are looking for a Senior AI Ops Engineer to join our AIOps team and help build the AI-powered platforms, agents, and workflows that enable engineering teams across our company.
This is a hands-on role for someone who can take AI solutions from idea to production, build the infrastructure around them, and create the observability needed to understand and improve how they behave in the real world.
Job responsibilities
Build and operate production-grade AI agents, AI-enabled tools, and workflows that empower developers and operational teams.
Design agentic systems using frameworks such as LangGraph, LangChain, and Supervisor, including RAG, MCP integrations, tool calling, and guardrails.
Build and evolve an AI SDLC harness that helps teams plan, implement, validate, govern, and safely deliver AI-assisted software changes.
Lead AI observability with Langfuse and OpenTelemetry, including tracing, evaluations, quality measurement, and cost analysis.
Build automated evaluation frameworks, including LLM-as-a-judge, to improve the reliability and quality of AI systems.
Design and maintain the infrastructure, CI/CD pipelines, GitOps workflows, and security controls that support AI services.
Develop internal developer tooling and automation that removes friction across the engineering organization.
Partner with engineering and product teams to turn real operational challenges into scalable AI-powered solutions.

As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.