דרושים » AI » AI Engineer

Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.

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 talented, creative, and fast-moving AI Engineer to join our AI team.
This is a unique opportunity to play a hands-on role in shaping the future of AI-driven technologies across our cloud data platform.
Were seeking a smart, creative, and fast-learning engineer who thrives in a dynamic environment.
A curious mind who loves to experiment, prototype, and transform cutting-edge AI and ML concepts into impactful, real-world products.
Responsibilities:
Design, develop, and deploy AI-based features and automation tools across our platform.
Collaborate with engineering, product, and data teams to identify and execute opportunities for AI integration.
Work with Machine Learning models, LLMs, NLP, and generative AI frameworks to enhance product intelligence and user experience.
Prototype, test, and iterate rapidly, optimizing models for scalability and performance.
Stay updated on AI and ML trends, tools, and research, bringing fresh ideas and technical insight to the team.

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

Required Al Builder - Performance
About the role (overview)
As part of our Business Technologies & AI organization, youll build and ship AI agents and workflows that drive measurable impact on our internal core business processes-and then own their performance over time.
Using our AI Gateway, Custom GPTs, and low-code/no-code tooling, youll orchestrate prebuilt actions, design robust prompts, and wire data flows across systems like Salesforce, Snowflake, Gong, ERP, and internal tools-without writing low-level API code.
You will also treat AI agents like a real workforce: defining how they are onboarded, measured, evaluated, and improved. Youll build the operating model, metrics, and evaluation solutions that keep our AI ecosystem powerful, safe, and cost-effective.
1) AI Solution Design & Development
Rapidly build, test, and deploy AI agents using the AI Gateway, Custom GPTs, and low/no-code tools.
Design scalable, secure, and reliable workflows with strong prompt patterns, evals, and canary tests.
Define new actions with Platform/Integrations when needed; ensure every agent has clear I/O, purpose, and a KPI.
2) Orchestration, Data, & Operations
Configure and chain actions; handle mapping, preprocessing, errors, retries, and safe context assembly.
Use managed auth/secrets with least-privilege access and data minimization.
Write SQL for retrieval context, routing rules, golden sets, and performance queries.
Integrate logs, BI, and admin tools into a single operational view.
3) Performance, Quality & Evaluation
Define and track core metrics: usage, adoption, accuracy, cost, time saved, revenue impact.
Build dashboards, scorecards, leaderboards, and automated alerts (health, anomalies, regressions).
Maintain evaluation frameworks and pipelines (golden sets, scenarios, automated checks).

We are looking for a Senior AI Software Engineer to help build and evolve AI-powered cybersecurity products that protect customers at global scale. In this role, you will design and implement intelligent systems leveraging AI agents and large language models (LLMs), partnering across engineering, security, and product teams to deliver secure, reliable, and responsible solutions.
This role requires strong software engineering fundamentals, hands-on experience building AI-driven systems, and a passion for applying cutting-edge AI technologies to solve complex security challenges.
Why Join Us
Youll be part of the Office of the CTO of our company Security, working on innovative, high-impact security products powered by AI that shape the future of cybersecurity. We foster a collaborative and inclusive culture that values a growth mindset, technical excellence, and continuous innovation.
Responsibilities
Design, develop, and maintain cutting-edge AI technologies and products within the Office of the CTO, from early prototypes to production-grade systems.
Build and evolve AI agent-based architectures, including multi-agent workflows and tool-using agents.
Apply advanced LLM design patterns to improve accuracy, robustness, and safety of LLM-powered systems, including prompt engineering, flow engineering, Retrieval-Augmented Generation (RAG), self-review, ReAct, and guardrails.
Write high-quality, secure, and maintainable code primarily in Python, following modern software engineering best practices.
Collaborate with cross-functional teams, including product, research, and security, to define requirements and deliver end-to-end AI solutions.
Identify and resolve reliability, performance, and security issues in AI-enabled services.
Contribute to architecture and design reviews, ensuring solutions meet security, privacy, compliance, and responsible AI requirements.
Mentor other engineers and contribute to a culture of engineering excellence and continuous learning.

We are seeking a highly skilled AI Engineer to help define the future of intelligent forensic research platforms.In this role, you will lead the design and integration of advanced AI capabilities into a large-scale, production-grade environment, working closely with core engineering and research teams.
You will contribute to unifying internal tools and workflows into a cohesive, AI-driven ecosystem that significantly enhances developer and researcher productivity.You will also drive the evolution of automation and analysis pipelines, replacing brittle processes with robust, scalable, and intelligent solutions.
A key part of the role involves exploring complex datasets, evaluating models, and applying generative AI and heuristic approaches to uncover, structure, and interpret digital artifacts.This position offers the opportunity to work on challenging problems at the intersection of AI, systems engineering, and data analysis, with real influence over architecture, tooling, and research direction.
If you are motivated by building high-impact AI systems, solving non-trivial technical problems, and enabling teams to operate at a higher level, this role provides a unique opportunity to make a lasting impact in a mission-driven domain.
Key Responsibilities:
Develop and implement AI solutions to parse and analyze data from forensic extractions, including mobile devices.
Design, build, test, and maintain efficient, reusable, and reliable C# .NET code with integration to cloud services in AWS.
Utilize heuristic-based methods and GenAI technologies to enhance data identification and classification.
Research, explore data, assess, and implement the best models to solve various forensic research problems.
Collaborate with other professionals across the company, combining AI, Forensic Research, and Engineering expertise.
Translate forensic research methods into AI algorithms and innovation suggestions.
Location - Israel, Petah.

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.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.
In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.
You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.
If you enjoy working at the intersection of AI and engineering - bringing models to life in production, optimizing for performance, and building reliable systems - this role is for you!
Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models.

We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world production-grade AI systems and ML pipelines to join our AI group. You'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. Youll work closely with data scientists to translate research into scalable solutions and manage model deployment in both cloud and on-prem GPU environments.
:Responsibilities
Design, build, and deploy production-grade ML models, AI agents, and end-to-end pipelines across cloud and on-prem GPU environments.
Maintain and optimize ML systems for performance, scalability and reliability, including model validation, inference speed, and resource efficiency.
Develop monitoring and observability tools such as alerts and performance metrics to ensure system stability in production.
Create and integrate APIs for ML services within microservice-based architectures.
Drive adoption of best practices for CI/CD, observability, and reproducibility in ML systems.

we are a fast-growing AI powered mobile games publishing company by Unity. We work with game studios worldwide to help them build, scale, and operate successful mobile games using cutting-edge technology.Were looking for a Staff AI Engineer to join our growing AI and engineering group. This is a highly impactful role for someone who wants to shape how AI is embedded across products, platforms, and business operations-from early experimentation to production-scale systems.
As a Staff AI Engineer, youll operate end-to-end: identifying opportunities, designing solutions, and delivering real business value using modern AI and LLM-based systems.
What you'll be doing:
Design, build, and deploy AI-powered solutions across Supersonics products and internal platforms
Partner closely with product, data, engineering, and business stakeholders to identify and execute high-impact AI use cases
Architect and implement agentic workflows using frameworks such as LangChain, LangGraph, or equivalent
Integrate and operate LLMs via SDKs, including prompt design, structured outputs, tool/function calling, and guardrails
Lead technical decisions around AI evaluation, monitoring, observability, and quality measurement
Own AI initiatives from concept through production, including iteration, scaling, and long-term maintenance
Stay up to date with emerging AI technologies, models, and best practices, and help bring them into production thoughtfully