לוח משרות דרושים AI Engineer משרה מלאה, לחיפוש זה נמצאו 140 משרות

we are looking for a Senior AI Software Engineer to join our Generative AI foundation team. We build AI agents and shared infrastructure that power GenAI capabilities across the company, enabling CyberArks product lines to adopt agentic workflows safely, reliably, and at scale. In this role, youll be involved in the full software lifecycle - from fast-moving prototypes and POCs to production-grade, observable systems. Youll collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence. Youll work hands-on with leading LLMs and the modern agentic ecosystem, leveraging a wide range of AWS services. Youll use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve our solutions through solid design, flexible implementation, strong telemetry and evaluation, and production feedback loops.
Your Impact:
Design, develop, and deploy scalable AI agents and shared infrastructure for GenAI capabilities.
Manage the full software development lifecycle, from prototyping to production-grade, observable systems.
Collaborate with product managers, researchers, and engineers to translate ideas into robust and scalable services.
Work hands-on with large language models (LLMs), agentic frameworks, and a broad range of AWS services.
Implement strong telemetry, evaluation metrics, and feedback loops to continuously improve AI solutions.
Champion operational excellence through pragmatic experimentation, iteration, and solid design.

We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today.
Key Responsibilities:
Develop internal AI-powered products and tools used by teams across to work faster and smarter.
Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams.
Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows.
Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development.
Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption.
Work hands-on with the most advanced AI development tools and shape how the company uses them.

Required AI Engineer
Why is this role so important?
As an AI Engineer, you will be a key player in building our new AI platform, AI Studio. This platform aims to provide users with instant answers to complex market research questions, generate world-class reports, and create live, interactive, and powerful dashboards. Our goal is to reduce the complexity and time-to-insight for our users, helping them streamline their market tasks and achieve automation that drives real value.
So, what will you be doing all day?
Design and develop LLM-based intelligent agents that can handle complex market research queries.
Utilize LangGraph and other frameworks to create state of the art AI agents that integrate various tools and data sources.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with product, data, and UX teams to ensure that AI solutions are aligned with user needs and business goals.
Continuously evaluate and improve the performance of AI models to ensure high-quality and data-driven results.

In this role, you will define and deliver AI solutions that unify data across our infrastructure and engineering systems, enabling advanced analytics for production engineering teams through AI agents, copilots, and workflow automation. You will own solutions end to end, from architecture and development through deployment, maintenance, and continuous improvement, and help shape how ASIC networking product engineering uses AI to scale engineering productivity.

What you'll be doing:

Design, build, and maintain AI solutions that improve our division efficiency across production, characterization, analysis, and operational workflows.

Develop agentic analytics capabilities that enable engineers to query, analyze, and reason over ASIC data using AI agents and copilots.

Consolidate data from multiple infrastructure and engineering systems into scalable, reliable pipelines and reusable services.

Partner with production engineering teams to identify pain points, define high-value use cases, and deliver measurable impact.

Build and support tools for data access, automation, reporting, anomaly detection, and engineering insight generation.

Collaborate across our to align interfaces, improve data quality, and support scalable deployment models.

Drive continuous improvement through user feedback, monitoring, and roadmap planning.

abra professional services is seeking for an AI Engineer (GenAI & Integration) The AI Engineer (GenAI & Integration) designs, builds, and deploys AI-powered solutions within enterprise systems and business workflows. The role focuses on practical application of AI by integrating models, data, and tools into real operational environments to enable automation, decision support, and productivity gains. The role emphasizes implementation and integration rather than model development, bridging AI capabilities with enterprise systems and workflows. Key Responsibilities
* Design and implement end-to-end AI solutions aligned with business needs
* Integrate AI capabilities with enterprise systems, APIs, and data platforms, including legacy environments
* Develop AI agents and automation workflows for multi-step task execution
* Build AI-driven applications, including copilots and decision-support tools
* Develop and maintain integration layers, including MCP-based and similar AI integration services
* Evaluate, test, and validate AI outputs to ensure accuracy, reliability, and quality in production
* Deploy, monitor, and optimize AI solutions in production environments
* Maintain clear and structured documentation across solutions, integrations, and processes
* Lead implementation of AI solutions in collaboration with business, IT, and engineering teams to ensure scalable and compliant delivery

we are 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.
we are 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.
Qualifications
Your Impact
Design and implement automated evaluation loops, static analysis, and rigorous quality gates to ensure the ADLC process doesn't just write code, but consistently produces great, production-ready code.
Help the team tackle complex, hard problems to elevate our autonomous development product from "good" to "excellent".
Lead complex initiatives in Context Engineering and Prompt Engineering.
Manage and orchestrate the complex ecosystem of autonomous agents utilized for internal development.
Serve as a leading individual in a very strong team professionally and personally - Were looking for someone who not only delivers his own work but improves that of those around them.
Find space for growth to push the entire team or group forward - New projects, changing processes or improving existing tools.
View prompt engineering as a core engineering discipline-where rewriting agent behavior is a versioned, reviewed, and tested code change.
Act with a debugging temperament; conduct deep-dive analyses of raw agent transcripts to diagnose non-deterministic failures and ascertain root causes instead of merely working around them.

This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production - owning outcomes end-to-end, including deployment, monitoring, cost, and business impact.

We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI.

What You Will Build
AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role - not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space.
Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requests as a risk to momentum. Use feature flags, canary releases, and rollback architecture to manage risk through isolation - not through avoidance.
AI-Augmented Engineering Workflow. Leverage AI-assisted development tooling (code generation, automated testing, architecture prototyping) as a core workflow multiplier. Evaluate and experiment with emerging AI tools and frameworks with direct hands-on engagement. Bring technical depth to AI fluency - architecture and capability tradeoffs, not surface-level awareness.
End-to-End Ownership. Own your work from design through production deployment, operational monitoring, and business impact measurement. Accountability extends beyond the feature to CI/CD pipeline health, observability, cost efficiency, and domain-level outcomes.
Architectural Decision-Making. Make pragmatic, timely architectural choices that balance modern AI and data technologies with reliability, cost, and delivery speed. Distinguish reversible vs. irreversible decisions and move forward without waiting for consensus on the former. Document decisions in lightweight ADRs and own the outcomes.
Cross-Functional Collaboration. Partner with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions. Operate with business awareness - understand how your systems impact revenue, customer outcomes, and strategic priorities.

We are seeking an Senior AI Engineer to design, build, and deploy AI-powered capabilities within our product.

This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.

The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure. transforming AI technologies into practical applications.

Responsibilities:
Build applications powered by machine learning and large language models (LLMs).
Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.
Integrate AI functionality into backend services and product workflows.
Design and implement retrieval pipelines, embedding pipelines, and inference workflows.
Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.
Create scalable AI architectures capable of handling production workloads.
Package and deploy AI models as production services.
Optimize inference performance, scalability, and latency.
Monitor AI services to ensure reliability and performance.
Develop backend services and APIs that expose AI capabilities.
Integrate AI systems with databases, internal services, and external APIs.
Contribute to system architecture and microservices design.
Implement logging, metrics, and observability for AI systems.
Track model performance and system reliability in production environments.
Work closely with product managers, engineers, and data scientists.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.
What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements

We're looking for a Senior AI Infrastructure Engineer to join a group that specializes in Security and Networking, and specifically ML/AI, MLOps, and agentic AI development. As a Senior AI Infrastructure Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, and security architects to ensure smooth development, deployment, evaluation, and optimization of AI pipelines, models, and agents. This role requires a balance of high-level engineering rigor and a collaborative spirit; youll be a technical anchor and a supportive peer for teams across the organization.



What youll be doing:

Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production.

Managing ML/agentic workflows to ensure performance, high availability, resource efficiency, and cost-effectiveness.

Designing and implementing pipelines and frameworks for AI training, inference, and experimentation.

Partnering with data scientists and security architects to operationalize AI agents, including packaging and integration with existing systems. This includes contributing to and reviewing code, design documents, and test plans.

Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes, ensuring reliable deployments and rollbacks.

Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production.

Implementing access controls, authentication mechanisms, and encryption standards to keep our AI models and data secure.

Documenting guidelines and leading knowledge-sharing sessions to elevate the teams collective development expertise.

We are seeking a Senior AI Engineer to join a talented and fast-moving AI Engineering team. We're the central hub for AI across, driving innovation and putting AI to work for every team and product in the company.
AI already plays a foundational role in how we operate. It lets us ship features quickly and at scale, equips non-technical team members with tools that boost their productivity, and underpins much of the innovation happening across the company today.
If this kind of environment excites you - and if you believe great engineering means crafting the most effective and elegant solution within real-world constraints - we'd love to hear from you.
What You'll Be Doing:
Design, build, and maintain reusable AI capabilities - spanning models, tools, APIs, and platforms that support both internal operations and customer-facing products.
Develop and maintain our internal MCP server, giving AI agents easy and secure access to our extensive data stores.
Create and implement rigorous evaluation frameworks and AI guardrails to protect our value and ensure model reliability.
Cultivate deep expertise and establish sustainable AI engineering practices across the organization.
Champion AI readiness and track adoption company-wide to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Own projects end to end - from gathering requirements from non-technical stakeholders through development, deployment, and ongoing operation.
Serve as a consultant and advocate for AI engineering, guiding other teams in leveraging the platforms and tools you create.
Collaborate with teams throughout to accelerate AI adoption and productization.

We're hiring a software engineer to work directly with our business teams - finance, sales, legal - building tools and automations that help them do their jobs better. You'll write production code and own what you build, but most of your time will be spent understanding business processes and how to impact them.
Most business teams have more day-to-day operational pain than they realize, and a lot more they could be doing with AI than they know. Your job is to find those gaps and build something that fixes them. Success looks like the team being able to move faster and spend their time on the work that matters, because everything else just runs.
You'll have a lot of autonomy in this role. You'll decide what to work on, build it, ship it, and see whether it actually made a difference. You'll be doing this as part of a small, senior AI team, so while the day-to-day work is independent, you'll have other engineers to collaborate with and a shared bar for how we build things.
What You'll Be Doing:
Build & Engineer:
Take the lead on technical implementation and be the owner of how it all works - picking the right tool for the job (code, no-code, or otherwise) and keeping the knowledge of the system in your handsDesign and deliver end-to-end AI solutions - from first stakeholder conversation through production deployment and iteration
Implement LLM-powered systems: RAG pipelines, AI agents, multi-step automations, and tool-integrated workflows
Integrate solutions with enterprise systems (Salesforce, NetSuite, Slack, Data platforms) and build for production: observable, reliable, and cost-optimized
Embed With the Business:
Work directly with Finance, Sales, HR, Legal, and Customer Success to identify and scope high-leverage AI opportunities
Translate ambiguous business needs into concrete engineering plans; own both the solution definition and the build
Help business stakeholders develop AI fluency and become stronger partners over time

We are looking for a highly skilled AI Engineer to join an advanced R&D environment within the security sector.
Responsibilities:
Develop advanced Python-based systems and integrate a variety of AI models into software solutions.
Implement and deploy AI models in On-Premise environments, including full integration within existing systems.
Work closely with a multidisciplinary team in a dynamic, innovative technological environment.

We're hiring an exceptional Applied AI Scientist to join our team!

In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across Tipalti's core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.


In This Role, You Will Be Responsible For


Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

As a member of our fast-paced group, youll have the unique and rewarding opportunity to shape the future. We are looking for people with excellent applied machine learning, NLP experience and solid engineering skills.

This role will have the following responsibilities:
Developing and integrating AI systems (e.g RAG, agents) into deliverable products.
Developing and evaluating domain specific Large Language Models for various tasks and applications.
Understanding product requirements, translating them into modeling tasks and engineering tasks.
Collaborating with Hardware and Software teams across us.
Translating theoretical ideas into tangible innovations.