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Required Software Engineer - Al Platform
About Us
We help modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, weve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over ~4500 midsize and multinational companies and over 1 Milion users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
What this role is really about
Were building our internal AI Platform as a foundation that enables safe, scalable, and cost‑effective AI across the company. Our mission is to support internal business units in becoming more productive and driving business growth. As a Software Engineer on Business Innovation (Internal), youll develop high‑leverage platform capabilities used by Product, Customer Success, Sales, Operations, Data, and IT. Youll work across the entire stack, from APIs and services to data and UI. transforming business requi
Build core AI platform services - Design and implement agent orchestration, prompt management, RAG, Connectors, and evaluation pipelines that power AI experiences across the company.
Develop complex agentic workflows - Develop a multi-step workflow that coordinates tools and services with proper observability, guardrails, and cost controls (using OpenAI Agent SDK, LangGraph, or a similar framework).
Build LLM evaluation and optimization systems -Develop evaluation harnesses, offline/online experiments, prompt-testing frameworks, and dashboards to balance quality, latency, and spend across all AI services.
Ship the internal AI portal - Build user-facing products that democratize AI access: prompt directories, agent designers, templates, approval workflows, and more.
Ensure security and compliance - Develop RBAC, data classification, PII redaction, audit logging, and policy enforcement.
Create robust integrations - Connect the platform with Salesforce, NetSuite, Slack, Snowflake, HRIS, and other critical business systems.
Establish operational excellence - Implement CI/CD, testing strategies, monitoring/tracing, and SLOs for high-reliability services.
Enable developers - build SDKs, CLIs, and templates that help teams create safe, scalable AI workflows. Lead technical discussions and write design documentation.

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

As an AI Engineer, youll build full-stack features that deliver seamless user experiences combining robust engineering with advanced AI capabilities.

Responsibilities
Design and deploy agent-based systems for real-world use cases
Build end-to-end features: backend APIs, data models, and React-based UI
Integrate AI and agentic logic into the core product
Develop backend pipelines for autonomous agents and workflow automation
Optimize model accuracy, reliability, and performance
Work closely with product, data, and UX teams to align AI with business and user needs

Required AI/ML Engineer AI Foundations Group
Tel Aviv Full-time
About The Position
Our AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
Our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Job
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 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.

We are seeking a Product Manager for AI Platform, to lead most critical evolution: the transformation to an Agentic Platform.

This role operates as a "Startup within a Startup." You will own the end-to-end AI domain, from building the underlying technical infrastructure to launching the interfaces our customers interact with.

You will drive the entire product lifecycle: bringing innovative ideas to the table, executing on early versions, and collaborating closely with internal teams and design partners to validate value. Your ultimate goal is to mature these capabilities from early concepts into core platform standards, driving mass adoption across our entire user base.

You will serve as the knowledge center for the organization, guiding how the entire platform must evolve to support the next generation of autonomous engineering.

What You Will Be Doing

Lead AI product domain from ideation to launch of customer-facing AI interfaces and agents
Design and manage AI Agents platform, enabling customers to create, manage, and run AI agents
Drive ecosystem initiatives to make the platform native to agents through API improvements, MCP integration, and agent-accessible protocols
Define strategic direction for making "AI-Native," guiding data architecture for effective AI agent interaction
Own product roadmap and prioritization, balancing immediate needs with long-term Agentic architecture investments
Advocate across product and R&D teams to integrate AI-native interfaces and drive AI-first development mindset
Identify high-impact opportunities through customer discovery and experimentation with cutting-edge AI technologies
Collaborate with engineering and design to translate AI capabilities into intuitive, trust-building user experiences
Analyze adoption metrics and feedback to optimize AI performance and increase trust in autonomous workflows
Act as company AI center of excellence, enabling Sales, Marketing, and CS teams to articulate Agentic Engineering value

we are seeking a highly skilled Senior AI Engineer to design and implement complex, multi-agent systems powered by LLMs.
In this role, you will build and orchestrate AI agents using LangGraph and LangChain, manage stateful conversations, and support scalable RAG pipelines that connect external knowledge sources to reasoning agents. Youll work closely with product and backend teams to deliver real, production-grade AI capabilities.
Responsibilities:
Agent Orchestration: Design, build, and maintain networks of LLM-powered agents that collaborate, share context, and reason together to execute complex workflows.
LangGraph Architecture: Implement and manage LangGraph graphs that handle message memory, context persistence, and multi-step task coordination.
RAG Pipelines: Optimize RAG systems to enrich agent reasoning with relevant, up-to-date information.
Prompt & API Composition: Build modular prompt templates and API calls that agents use for reasoning, retrieval, and action execution.
Integration & Deployment: Work with engineers to integrate the agentic framework into production systems via APIs and backend services.
Evaluation & Iteration: Implement evaluation frameworks to measure performance, reliability, and consistency of AI responses across multi-agent pipelines.
Cross-Team Collaboration: Partner with product and engineering teams to align AI behaviors with real user workflows and KPIs.

As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our companys 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.

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.

Were hiring a ML Engineer to accelerate AI-driven innovation across B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do.:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.