דרושים » AI » Senior Product Manager, Autonomous Squad

As an AI Developer on our Optimization team, you will play a key role in advancing our core optimization capabilities by infusing them with cutting-edge artificial intelligence.

Our team is on a mission to significantly enhance our existing, high-performance optimization engine. You'll tackle a diverse range of complex problems - including optimization of vehicle routing and scheduling - for our customers at a massive scale.

You will join our team at a pivotal moment and be an integral part of building our next-generation AI/ML capabilities from the ground up. As a key contributor, your responsibilities will span the entire model lifecycle, from augmenting our current optimization models with advanced AI to implementing the infrastructure for their deployment and monitoring.

You will apply state-of-the-art techniques such as Deep Reinforcement Learning (DRL), predictive analytics, and Graph Neural Networks (GNNs), all while working with rich datasets including Geographic Information System (GIS) data.

Another core part of your role will be implementing best practices for safe AI/ML rollouts. You will help build and maintain robust A/B testing frameworks and canary deployment strategies, ensuring our innovations reach production safely and effectively.

In this highly collaborative position, you will work closely with other engineers and scientists, as well as cross-functional product teams in the US, to bring these intelligent services to life.

Responsibilities:

Develop, implement, and deploy state-of-the-art optimization models and machine learning algorithms to solve complex business problems like vehicle routing and resource scheduling.

Design and build robust, end-to-end MLOps pipelinesfrom data ingestion and feature engineering to model training, validation, and serving in a production environment.

Translate complex scientific concepts and research papers into production-quality code, primarily using Python and leveraging frameworks like PyTorch and optimization libraries.

Conduct rigorous offline and online experiments to validate model performance, ensuring that solutions are statistically sound, reliable, and deliver measurable business impact.

The AI Transformation Architect plays a central role in driving our companys enterprise-wide AI transformation. Reporting to the VP of AI Transformation, this role defines and builds the technical and architectural foundations that power our AI-driven software organization.
The Architect leads the design and implementation of scalable Generative AI platforms and central services for AI, creating shared capabilities, tools, and frameworks that transform how our company builds, delivers, and operates products.
Beyond architecture, this role drives strategic, high-impact projects with powerful ROI that positively disrupt operations and elevate customer outcomes, improving efficiency, innovation, and product value across the company.
Strategic Objectives
Accelerate AI Transformation across the SDLC by designing and operationalizing central AI services and a unified platform framework that powers key transformation initiatives, including Agentic Workflows.
Institutionalize AI Engineering and Governance Standards through common architecture, services, and enablement frameworks ensuring scalability, security, quality, and compliance.
Deliver measurable transformation outcomes through strategic, ROI-driven projects that reshape how our companys products are built and operated, directly benefiting customers and business performance.
Drive sustainable transformation at scale, balancing rapid innovation with operational excellence and long-term maintainability.
Key Responsibilities
Architect the AI Transformation Framework
Design and own the end-to-end architecture that enables the companys AI Transformation vision - spanning data, models, pipelines, APIs, and governance layers.
Define blueprints and integration standards to embed AI and automation throughout the SDLC, from ideation to delivery.
Build Generative AI Platforms and Central Services
Lead the design and implementation of the AI Enablement Platform and central AI services powering transformation initiatives such as Agentic Workflows and the Knowledge Hub.
Create scalable, secure, and modular AI components that can be leveraged across product lines and engineering domains.
Partner with infrastructure, platform, and security teams to operationalize LLM-based services, retrieval systems, and agentic automation flows.
Drive Strategic Transformation Projects
Lead cross-functional initiatives that deliver tangible operational and business impact - improving speed, quality, and cost-efficiency across the product organization.
Develop strong business cases and ROI frameworks to prioritize and communicate transformation value at the executive level.
Translate successful outcomes into reusable playbooks and AI cookbooks that scale across teams, roles, and product domains.
Technical Leadership and Enablement
Act as the senior technical authority and coach for AI transformation initiatives, guiding teams through architecture reviews, proofs of concept, and scale-up phases.
Mentor internal architects and tech leads to develop AI-native architectural competencies.

About the Role We are building an AI-driven future at our company, and we need an exceptional AI Engineer to join our new AI Department. This is a unique opportunity to work in a startup environment within a growing company, where youll take ownership of AI and ML initiatives, build cutting-edge solutions, and influence the direction of our AI products. The role has strong leadership potential and is suited for individuals who are passionate about solving complex problems and making a real impact. What Youll Do
* Research, design, and implement LLM-based products and infrastructure.
* Collaborate with data scientists, data engineers, product teams, and backend engineers to integrate AI solutions into products.
* Take full ownership of AI engineering pipelines from experimentation to production.
* Utilize cloud-based AI deployment strategies, particularly within AWS.
* Develop and maintain high-quality, scalable, and efficient code.

When leading companies choose our company Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use our company Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales our companys by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to our company Cloud products.
As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate our company Cloud to our customers. You will help prospective and existing customers and partners understand the power of our company Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on our company Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply the impact of the team as a whole.

our Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our companys cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to our company Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to our company Cloud.
Work directly with our company Cloud products to demonstrate and prototype integrations in customer and partner environments.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of Lemonades data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives Lemonade toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.

In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams

Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights

Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance

Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights

Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions

Collaborate closely with other Staff Engineers across Lemonade to align on cross-organizational initiatives and technical strategies

Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions

Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization

We are seeking a proactive and detail-oriented Customer Success Automation Engineer to join our growing team. The ideal candidate will have a strong technical background combined with a passion for enhancing customer experience through automation. This role will focus on developing and implementing automated solutions to streamline customer success processes, improve efficiency, and drive customer satisfaction.
Key Responsibilities
Develop and Implement Automation Solutions: Design, develop, and deploy automated workflows to optimize customer success operations.
Process Improvement: Identify opportunities for automation within customer success processes and implement solutions to improve efficiency and customer satisfaction.
Technical Support: Provide technical expertise and support to the customer success team in utilizing automation tools and systems.
Data Analysis: Analyze customer data to identify trends, patterns, and areas for improvement. Use data insights to drive automation strategies.
Collaboration: Work closely with cross-functional teams, including Customer Success, Product, and Engineering, to understand customer needs and develop appropriate automated solutions.
Documentation: Create and maintain documentation for all automation processes and workflows.
Training and Support: Train and support customer success team members on new automation tools and processes.

Harmony SASE is building the next generation of secure access services enabling organizations to connect users, sites, and applications safely and seamlessly from anywhere.
As part of our ongoing innovation, were expanding our capabilities around AI-driven development and automation. The Dev AI Infra & Tools team leads this transformation building the internal platforms and tools that empower our engineers to design, test, and deliver faster, smarter, and more securely.
Youll work hands-on with Generative AI frameworks and agents, developing the systems and integrations that change the way our engineering teams work.
Key Responsibilities
Design and build AI-driven internal tools that enhance developer productivity.
Develop and maintain the infrastructure supporting GenAI agents and automation frameworks.
Prototype and experiment rapidly, turning ideas into practical solutions.
Collaborate with DevOps, backend, and product engineers to identify and implement high-impact GenAI use cases.
Evaluate new Generative AI and agent-based technologies and integrate the most promising ones into production.
Define and track efficiency metrics to continuously improve developer velocity and experience.

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 featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith 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.

The GenAI team builds conversational experiences that feel human and decision engines that learn on their own. If moving from prototype to production with millions flowing through it gets you buzzing, keep reading.

In this role you'll:
Design, build, and own end-to-end Generative-AI services from first prompt to production rollout

Combine retrieval-augmented generation (RAG), function calling, and agents to automate underwriting, claims, and customer support flows

Fine-tune open-source and commercial LLMs on proprietary datasets, evaluate with both offline benchmarks and online A/B tests

Collaborate with product, data science, and design to invent new AI-first customer experiences (and kill the bad ones fast)

Build scalable APIs and micro-services (TypeScript/NestJS or Python/FastAPI) running in Kubernetes on AWS

Instrument, monitor, and continuously improve model quality, latency, and cost you ship it, you own it

Mentor fellow engineers on GenAI best practices: prompt engineering, vector search, safety & guard-rails

Contribute to internal tooling that automates the boring stuff (CI/CD, sandbox environments, branch deploys)

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.