לוח משרות דרושים הייטק AI

We are seeking a skilled Backend Engineer to join our team and implement advanced AI solutions in our travel and expense management products. The ideal candidate will have strong backend engineering expertise and enthusiasm for working with cutting-edge AI technologies.
You'll be responsible for designing and implementing backend services that integrate AI capabilities including large language models (LLMs), retrieval-augmented generation (RAG), and conversational interfaces into our consumer-facing products. This is an opportunity to expand your expertise into AI while leveraging your strong engineering foundation.
What Youll Do
Design and develop scalable, high-performance backend services and APIs.
Implement integrations with AI platforms and services.
Work with AI specialists to translate AI capabilities into production-ready features.
Ensure high reliability, performance, and security of AI-powered systems.
Collaborate with product and engineering teams to gather requirements and deliver solutions.

At our company, we aren't building a single, generic chatbot. We are building a Composable AI Microservice Architecture, a swarm of hundreds of hyper-specialized AI services, each meticulously "programmed" to solve small, focused tasks with high precision. This fleet powers Ava, our AI support engine, and a suite of cutting-edge generative tools for travel and expense management.
As a Senior AI Ops / MLOps Engineer, you are the architect of the platform that makes this scale possible. You will move beyond traditional MLOps to manage a "factory" of Language Models. Your challenge is one of orchestration and standardization, ensuring that every service in the swarm meets a rigorous bar for quality, reliability, and cost-efficiency.
What You'll Do
Orchestrate the AI Fleet: Build and own the runtime environment for 100+ specialized AI services. Manage model routing, context versioning, and standardized memory/history stores.
High-Density Inference Optimization: Design and implement SageMaker Multi-Model Endpoints (MME) and Inference Components to serve multiple tuned SLMs per GPU, maximizing hardware utilization while minimizing latency.
Deterministic Service Excellence: Treat reliability as a layered engineering problem. Build deterministic "shells" around probabilistic LM outputs, prioritizing data-layer validation and strict serialization.
Automated Evaluation & Observability: Implement "LLM-as-a-judge" patterns and automated benchmarking to detect semantic drift and hallucinations across the fleet before they impact the user.
Standardize the Workflow: Obsess over building reusable patterns and Terraform-based infrastructure that eliminate "snowflake" configurations, allowing us to deploy new specialized AI tasks in minutes.
Agency Strategy: Partner with AI Researchers to find the "Goldilocks zone" for agentic autonomy-balancing the flexibility of LLM tool-use with the precision required for production stability.

The Vision
We believe that Software Engineering is the highest-leverage human workflow in the company. In an AI-native world, the bottleneck is no longer how fast we can type, but how quickly we can validate, iterate, and deploy. Engineering excellence is our ultimate competitive advantage. As a Senior Software Engineer for AI Assisted Engineering Support, you will build the "intelligence layer" for our development teams. You aren't just building tools; you are building agents that understand our codebase, our standards, and our intent. Your goal is to move the company toward a "Demo to Prod" reality where AI handles the boilerplate, the testing, and the initial PR generation, leaving humans to focus on architecture and high-level logic.
The Mission: Agentic Engineering
Consistent with our "Human Centric Workflows" philosophy, you will treat LLMs as programmable functions grounded in our specific codebase. You will build the specialized assistants that integrate into our IDEs and CI/CD pipelines to unblock developers, automate reviews, and ensure that "gold-standard" code is the default, not the exception.
What Youll Do:
Build AI Engineering Assistants: Develop and scale the internal agents that assist with code generation, automated refactoring, and documentation.
Enable the "Demo to Prod" Pipeline: Work on the technical implementation of tools that allow for one-shot workflows-moving from a prototype or a spec directly to a production-ready Pull Request.
Deterministic Engineering Evals: Drive quality by prioritizing determinism. You will build the serialization formats and retrieval systems (RAG) that give engineering agents the exact context they need from our repositories to be precise and useful.
Automated Code Stewardship: Create agents that help maintain our "Immune System"-automated drift detection, visual regression testing, and security scanning for AI-assisted contributions.
Systemic Optimization: Implement a culture of rigour. You will run experiments across different models and tools, using engineering-specific benchmarks to ensure our assistants are actually increasing velocity and quality.
Global Collaboration: Partner with the US and Israel-based teams to integrate your assistants into our global developer platform and telemetry frameworks.

We're looking for a senior AI Engineer with a strong backend background and deep experience building agentic AI systems to join our growing team.
Responsibilities:
Own the development of end-to-end AI agents, including both customer-facing agents and deep background agents. This includes designing agent architectures, building and maintaining agent tools, constructing and iterating on prompts, and continuously evaluating, operating, and improving the agent infrastructure in production.
Integrate large language models (LLMs) into production environments to enable autonomous task handling and decision-making.
Collaborate closely with engineering, product, and security teams to turn ambiguous problems and AI research into reliable, production-grade capabilities.

We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.
You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.
Architect and implement distributed services that power AI-driven applications.
Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.

We are looking for a Senior Software Engineer to join our growing Innovative DataEngine team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history. This organization is in the center of the hurricane created by the artificial intelligence revolution.
As a Data Pipelines Engineer, You will be building pipelines on top of the Insight Engine, a one-stop shop to build fully integrated AI pipelines. You will build new and innovative AI pipelines and applications as blueprints for customers and AI practitioners to use.
This is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, we take the cost and complexity out of deploying enterprise and AI infrastructure across data centers, edge, and cloud.

Alice is seeking a driven, detail-focused professional to become a vital part of our team as a Generative AI Analyst. In this role, you'll dive into the cutting-edge of technology, meticulously analyzing various content infringements to secure the new wave of Generative AI tools. Your duties will include collaborating with experts in diverse fields such as Hate Speech, Misinformation, Intellectual Property and Copyright, Child Safety, among others. Your tasks will involve writing adversarial; prompts to identify weaknesses in various AI models, including Large Language Models (LLMs), Text-to-Image, Text-to-Video, and beyond. You'll also oversee data management to guarantee the highest quality of outputs. Responsibilities
* Developing adversarial and risky prompt strategies across several areas of abuse to expose potential vulnerabilities in models.
* Managing projects end-to-end, from initial planning and oversight through quality assurance to final delivery.
* Handling extensive datasets across multiple languages and areas of abuse, ensuring precision and meticulous attention to detail.
* Ongoing investigation into new tactics for circumventing foundational models' safety measures.
* Working alongside diverse teams, engineering, product, policy, to tackle new challenges and craft forward-thinking strategies and resolutions.
* Promoting a culture of knowledge exchange and continual learning within the team.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

We are seeking a Senior AI Researcher Reporting to CEO . This role is pivotal, aimed at addressing some of the AI industry's most complex challenges. Senior AI Researcher will act as a versatile 'joker card' within the R&D, stepping in to expedite projects, solve bottlenecks, and provide specialized expertise as needed. This role is designed to minimize latency and accelerate outcomes across various technical domains within the company. The ideal candidate will have strong technical expertise, excellent coding skills, and the ability to solve problems effectively.
The role doesn't include managerial responsibilities but does involve close collaboration with internal teams and the capability to inspire and guide staff. As a professional authority within our teams, the Technology Director will improve quality and speed up problem resolution. Adeptness in analyzing complex issues quickly, switching contexts when needed, and fostering a culture of growth and technical excellence is also desired.

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment - you will go from reading papers to shipping production systems. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions.
A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.
Responsibilities:
Own the research-to-deployment cycle for predictive driving models - from literature review and prototyping through to production integration
Design, implement, and iterate on real-time predictive models, including vision-language models, motion prediction models, and inverse reinforcement learning approaches (e.g., imitation learning, reward recovery)
Collaborate on higher-level reasoning systems, contributing to vision-language-action models that handle complex edge cases and long-horizon planning
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar.

As a Senior AI Engineer on the Guardian Agents team, you will develop both our autonomous "digital employees" that execute security programs and the Control Plane that governs them. You will build a platform that allows customers to calibrate agents through conversation, ensuring human feedback is transformed into persistent organizational knowledge. By engineering these closed-loop systems, you enable agents to learn, evolve, and deliver accurate, goal-driven security outcomes at scale.
What Youll Do:
Architect Autonomous Agents: Build goal-driven agents for complex security tasks like false-positive reduction and automated triage.
Build the Control Plane: Develop the infrastructure for Human-in-the-Loop (HITL) feedback, natural language calibration, and stateful memory systems.
Engineer for Growth: Implement evaluation frameworks and "organizational memory" to ensure agents stay accurate and follow historical security precedents.
Bridge AI & Engineering: Collaborate in a "Core Pod" with Security Researchers and Data Scientists to turn raw security signals into scalable, productized agent behaviors.
Scale Data Pipelines: Integrate agents with Big Data foundation to ensure real-time context and tenant-safe execution.

This is a research‑first role focused on deeply understanding LLM internals to improve the security of AI agents. Youll design careful experiments on activations and interpretable features- e.g., probing, attribution & ablation/patching, representation‑geometry analyses-to uncover mechanisms behind jailbreak, indirect prompt injection, and other attacks. Then translate those insights into signals that can be used for detection and analysis of a model response.
The field of LLM interpretability at scale is exploding, with several major publications in the last months, and major opportunities for innovation.
What Youll Do:
Investigate model internals, including activation/features analysis, unsupervised clustering, discovery of directions in latent space, etc. It may also require training specific model parts to improve interpretability metrics.
Design security‑grounded evaluations: curate datasets for different attack types, evaluate performance of different white box (model internals) methods compared to black box (input/output only) baselines.
Publish and share: produce Labs posts and open artifacts; when the work is strong, aim for tier‑1 ML venues (NeurIPS, ICML, etc.) and security forums. A publication of code and/or trained models in cases of community relevant novelty.
Build tools: Several open source libraries exist (like Anthropics attribution graphs infra), but the research in the field is very dynamic, which will require you to build and adapt tools to your own research directions. This also includes agents to automate research work and distill knowledge from designed experiments.

abra R&D is looking for a AI Evaluation & Reliability Engineer (Agents & LLM Systems)! abra R&D is looking for a AI Evaluation & Reliability Engineer who will take part in building the next-generation agentic analytics platform, the first real-time database optimized for AI agents at scale. We’re looking for a Senior AI Evaluation & Reliability Engineer to define and build how AI agents are measured, validated, monitored, and improved in production. This role sits at the intersection of LLM systems, evaluation research, and production-grade engineering. You will design evaluation methodologies, build LLM-as-a-judge systems, and develop agent-based testing frameworks to ensure correctness, robustness, and reliability of complex multi-agent workflows operating on real-time data. What You’ll Do:
* Design and implement evaluation frameworks for AI agents and multi-agent systems
* Build LLM-as-a-judge pipelines to assess correctness, reasoning quality, and output quality
* Develop agent-based evaluation systems (agents evaluating agents) for scalable testing
* Define metrics, benchmarks, scorecards, and methodologies for agent reliability and performance
* Build data-driven evaluation pipelines using synthetic and real-world datasets
* Identify and analyze failure modes, edge cases, and non-deterministic behaviors
* Improve agent robustness, consistency, and reliability in production environments
* Work with tools such as Google ADK, Opik, and related evaluation frameworks
* Collaborate closely with AI, platform, and database teams to shape agent–data interaction quality

we are a global leader in space based intelligence solutions, serving for over 20 years as a trusted partner to some of the worlds most demanding defense and intelligence organizations. The company delivers high quality, mission critical capabilities tailored to address complex, strategic, and highly sensitive intelligence challenges. As part of its continued growth, ISI is seeking a talented Algorithm team leader to join the Algorithm Development Group and lead cutting edge AI and Computer Vision initiatives that transform advanced research into operational impact. This position combines technological leadership, research direction, and end to end implementation in a production oriented environment.
Responsibilities:

* Professional and managerial leadership of an AI algorithm team
* Development, training, and optimization of Deep Learning models for computer vision tasks
* Hands on work with advanced detection and segmentation architectures, including YOLO
* Research and implementation of VLM and LLM in multimodal contexts
* Designing research workflows, experimentation frameworks, validation processes, and performance improvements
* Mentoring and guiding junior team members and supporting their professional growth
* Close collaboration with software, product, and hardware teams
Advantages:

* Experience working with GIS systems and geospatial data
* Experience implementing algorithms on hardware or working closely with hardware teams
* Experience optimizing models for real time systems or resource constrained environments
* Experience transferring models from research environments to production

Required AI consultant
Responsibilities:
As an AI Consultant and a CS team member, you will work at the technological forefront of the data analytics world by helping our customers adopt and realize business value through AI and Machine Learning. As a CSM you will be the customers key strategic advisor and implementer and you will work with senior stakeholders to:
Identify AI opportunities
Frame and size the value and the business impact AI can help customers realize
Drive the implementation of our software and services by collaborating and managing a cross-functional account team
Ongoing account management and commercial success including value realization analysis, Quarterly Business Reviews (QBRs), Pilot process management, etc.,
Gradually develop business-ML expertise and lend this SME towards our customers and our internal product development
Together with the team, you will continuously help our customers achieve their business goals, reinforce the value of our models, and the ease of using our platform.
When our clients are happy because they see the value, so are we!
The ideal candidate will be value-oriented, enjoys working with customers, analytical and consistently looking to improve their skills.