לוח משרות דרושים AI Engineer

abra R&D is looking for a AI Engineer! abra R&D is looking for an AI Engineer that will take part of building a next-generation agentic analytics platform powered by a real-time, AI-optimized data infrastructure. We are looking for an experienced AI Engineer to design, build, and deploy intelligent systems that operate at scale and in real time. This role is hands-on and product-oriented, focusing on developing, integrating, and productionizing AI and machine learning models as part of a complex, high-performance platform. What You Will Do:
* Design, develop, and deploy AI and machine learning models into production systems
* Build scalable AI services that operate on large-scale and real-time data
* Implement deep learning and machine learning solutions using modern frameworks
* Integrate AI models into end-to-end product flows and backend systems
* Collaborate closely with software engineers and AI teams to deliver production-ready solutions
* Optimize model performance, reliability, and scalability in real-world environments
* Develop and maintain data pipelines and model-serving infrastructure
* Contribute to the evolution of AI-powered, agent-based systems and analytics capabilities

As an AI Engineer on our team, you will own end to end development of systems and products, using AI intensively at every stage from architecture trough production.
You'll combine deep systems thinking with hands on technical excellence, collaborating closely with product, UX, and Data teams to turn business goals into scalable, production grade solutions.
This is an AI native role. We are looking for engineers who already work in a vibe coding workflow where AI tools are a core part of your daily development routine.

At our company, we build AI-powered vision systems that enhance safety and decision-making for some of the worlds largest vessels.
Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency.
Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions.
This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.
This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.
What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server)
Take models from research and turn them into production-ready, reliable components deployed on vessels
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew)
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems
Define and maintain clear interfaces between research code and production systems
Work closely with research and backend teams to integrate new models into production systems
Continuously improve system efficiency and reliability under hardware and runtime constraints.

our company, a software development company specializing in sophisticated e-commerce solutions, is looking for a motivated, talented, and skilled AI Officer. Our clients include leading brands such as McDonald's, Azrieli, Aroma Israel, Shlomo Group, Meshulam, Htzone, NewDeli, and more. This is a unique opportunity to showcase your talent, work with advanced technologies, collaborate with amazing colleagues, and support major customers.
Responsibilities:

* Monitor AI tools usage across the organization on an ongoing basis
* Ensure compliance with internal policies, procedures, and applicable AI regulations
* Review and approve requests for AI tool usage according to defined criteria
* Identify deviations, risks, and compliance gaps, and recommend corrective actions

Required Machine Learning Engineer - AI Coding Agents & LLM Infrastructure
Tel Aviv
Full-time
A bit about us:
We are redefining how software gets built. Trusted by over 1M+ developers, we build AI-first developer experiences powered by state-of-the-art coding agents and code reasoning models. With support for 30+ programming languages and 15+ IDEs, our platform is pushing the limits of LLM-based software engineering - enabling teams to design, write, review, and ship code faster than ever. Were committed to advancing code-native AI models, multi-agent systems, agent orchestration frameworks, memory, and autonomous dev tooling to empower developers at every step of the software lifecycle.
Were growing fast, and our team is passionate about pushing AI engineering to new heights - solving complex problems in LLM training, inference optimization, reasoning, and agent orchestration at scale.
About the Role:
As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our 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 hands-on, entrepreneurial Team Lead to take full ownership of Ollys knowledge systems and build one of the most critical pillars of the product.
Responsibilities:
Technical and managerial leadership of the Knowledge team
Designing and building production-grade knowledge systems at scale
Making architectural decisions and tradeoffs
(LLMs vs embeddings vs heuristics, online vs offline computation, cost vs latency)
Driving research, experimentation, and innovation around what knowledge means for AI Agents
Hiring, interviewing, mentoring, and growing the team
Working closely with Agent, Platform, and Product teams

You don't need a traditional technology background to succeed here. What we're looking for is someone who is genuinely passionate about AI, technically sharp, and capable of owning complex projects end to end. The technology operations side of the role is learnable; the drive, curiosity, and communication skills are not.
You'll be the person who shapes how uses AI internally, builds the systems that keep our technology running smoothly, and ensures our security and compliance obligations are met on time.
Responsibilities:
Gen-AI & Intelligent Tools
You'll own this from day one. we are actively building AI into how every team operates, and you'll be the person making that happen.
Continuously explore the generative AI landscape and bring forward clear, well-reasoned recommendations on what should adopt
Lead the full lifecycle of AI tool rollouts, from identifying the right solution, building the business case, managing the rollout, and driving adoption across teams
Build and automate workflows using AI and no-code/low-code tools that remove friction and free up people to focus on higher-value work
Become the internal go-to for anything AI related, running training sessions, writing guides, and helping teams get practical results from the tools they use
Track and report on the ROI and adoption of deployed tools, and adjust course when something isn't working
Stay obsessively current on what's happening in AI, new models, new agent frameworks, new use cases, and translate that knowledge into concrete action
Technology Operations
Take ownership of internal technology stack, including devices, software, user accounts, and day-to-day support
Manage employee onboarding and offboarding from a technology perspective
Keep SaaS tools, licenses, and vendor relationships organized and up to date
Maintain clear documentation so nothing lives only in your head
Security & Compliance
Keep ISO certification requirements on track by managing audit schedules, documentation, and coordinating evidence collection across departments
Drive SOC 2 readiness by maintaining the evidence library (access reviews, training records, change management logs) and supporting auditor visits
Vet new suppliers before onboarding by collecting security documentation, ensuring agreements are signed, and keeping the vendor register current

We are looking for a Junior AI Agent & Process Automation Analyst to join our Finance team and support a new initiative focused on mapping finance processes and embedding AI agents where they can add value. The role focuses on building autonomous AI agents that can understand their environment, use tools, and execute actions independently within defined finance processes.
Key Responsibilities
Map and document end-to-end finance processes in collaboration with Finance stakeholders.
Identify repetitive or manual finance processes with potential for AI agent automation.
Build and test AI agents that can autonomously perform defined finance-related tasks.
Configure agents to use tools such as APIs, internal systems, and data sources.
Validate outputs, monitor performance, and improve agent reliability over time.
Document agent logic, behavior, and learnings and share with stakeholders.

Were hiring an AI Engineer for our AI Core team to build and scale AI across products and workflows, from agentic document understanding to multi-agent systems and ML solutions. This is a hands-on, cross-functional role where youll prototype quickly, build robust evaluations, and ship production-grade AI with measurable business impact.
What youll do:
Build and ship AI/ML solutions using LLMs, agents, retrieval patterns (RAG), and document understanding models, alongside classic ML (classification, ranking, time-series).
Prototype and iterate quickly: turn ideas into high-quality POCs, validate feasibility, and evolve them toward production.
Shape technical direction and evaluate models and approaches using clear benchmarks, metrics, and real-world impact measurement.
Research and apply emerging techniques, e.g., multimodal/document AI, agentic frameworks, synthetic data generation, and architectural approaches.
Partner closely with product, engineering, and domain experts to identify opportunities and deliver end-to-end solutions.
Help shape scalable, secure architecture and best practices for AI delivery.
Location: Herzliya | Hybrid work model

We are looking for an AI-first Software Engineer who is highly product-oriented and excited about building customer-facing systems using modern AI tooling to dramatically increase development speed and operational automation.
What youll do?
Build and ship end-to-end product features (backend, frontend, integrations, automation).
Use AI tools and build the AI infrastructure to accelerate development through scalable workflows, including multi-agent approaches.
Build AI agents that fully automate customer-facing sales and service flows, in a business with a massive volume of textual interactions.

We are looking for an AI Enablement Tech Lead to lead the development of AI-native data capabilities and drive the adoption of AI across analytics workflows.
This role is part of the Analytics & AI Enablement group within the data department and is responsible for establishing the foundational data and AI capabilities that support advanced use cases, including chat with data, autonomous analytics, and AI-driven decision-making.
You will act as a technical and strategic bridge between data, engineering, and AI platform teams - owning the design of AI-ready data layers, and taking a significant part in the specification and orchestration of data-ready agent solutions and analytical workflows, from ideation to production.
You are a hands-on builder and a transformation leader, with proven experience delivering AI solutions and a strong foundation in data and analytics.
Hybrid
Full-time
What youll do: 
Define and build AI-ready data foundations, including semantic layers optimized for LLM and AI consumption
Design and standardize AI-native analytics workflows, combining data modeling, LLMs, and orchestration frameworks
Partner with Data Engineering and AI platform teams to shape infrastructure, tooling, and data interfaces for AI use
Drive experimentation with new AI capabilities and rapidly iterate from POC to scalable solutions
Establish best practices for AI usage in analytics, including prompt design, evaluation, monitoring, and governance
Act as a technical leader and mentor, driving AI knowledge and adoption across the analytics community.

- Drive technical decisions around AI evaluation frameworks, monitoring, and observability tools
- Design, build, and deploy AI-powered solutions across yad2s products and platforms
- Work hands-on with Large Language Models (LLMs), retrieval-augmented generation (RAG), embeddings, vector databases, and prompt engineering
- Develop scalable backend services that integrate AI capabilities into production
- Collaborate closely with product, data, and engineering teams to identify high-impact AI opportunities
- Lead by example: write clean, high-quality code, set best practices, and help shape the foundation of the AI team

We are looking for an experienced AI Automation Expert who will design, build, and maintain advanced AI driven workflows, internal agents, and process automations across the organization.
The ideal candidate has hands on experience with automation platforms such as n8n, Zapier or Make, strong technical understanding of modern AI models and APIs, and a proven record of translating business needs into scalable automated solutions.
This position plays a central role in our digital transformation efforts. You will be a partner with operations, support, engineering, and business leadership to streamline processes, reduce manual workload, and accelerate delivery through smart automation.
Responsibilities:
AI and Automation Architecture
Design and implement AI powered automations, including conversational agents, workflow orchestrations, and custom business logic.
Build and maintain automations using n8n, Flowgrammers, and similar workflow tools.
Create structured agent architectures using LLMs, vector databases, and contextual memory.
Develop and maintain reusable automation components and templates.
Process Design and Optimization
Map and analyze existing processes together with relevant stakeholders.
Identify opportunities for automation and propose clear technical solutions.
Implement end to end workflows from data ingestion to final output and quality control.
Ensure security, reliability, and compliance in all automated processes.
Systems Integration
Connect internal systems such as CRM, ERP, customer support tools, databases, and cloud platforms to automation workflows.
Integrate external APIs including OpenAI, Azure OpenAI, Google Cloud, or vendor specific APIs.
Build bridges between systems that were not originally designed to work together.
AI Agent Development
Design and deploy specialized agents for operations, sales, customer support, and engineering teams.
Implement context awareness, memory persistence, and custom tool calling for agents.
Optimize agent performance, latency, and accuracy.
Monitoring and Maintenance
Create dashboards and alerting for workflow health and performance.
Troubleshoot failures, scalability issues, and data inconsistencies.
Continuously improve existing automations based on usage and feedback.