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As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness speed and scale in the frameworks they already use.

We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with as a vector store, ML feature stores, and LLM-powered data applications.

columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real: building the robust, production-ready connectors that make the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do
Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
Drive the AI/LLM integration strategy: designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

Who We’re Looking For – The Team Lead & Architect We’re looking for an experienced, hands-on AI Engineering Squad Lead to lead the team building the AI agents, intelligent workflows, and decision-making systems powering Chargeflow’s products. This role combines technical and architectural leadership with people leadership. You’ll lead engineers, build alongside them, and own production systems that must operate reliably, securely, and at scale. Our AI platform brings together models, data, tools, business logic, and intelligent workflows to solve complex problems across the chargeback and fraud lifecycle. These systems must understand context, make decisions, and take action in real time and under uncertainty. This isn’t a pure infrastructure or AI research role, and it isn’t about building impressive demos. It’s about turning rapidly evolving AI capabilities into reliable, production-grade products with measurable business impact. If you’re looking to manage tasks and stay above the code, this probably isn’t the role for you. About Chargeflow Chargeflow is a leading force in fintech innovation, tackling chargeback fraud and the impact it has on online businesses. Born from a deep passion for technology and eCommerce, we’ve developed an AI-driven solution that helps merchants manage credit card disputes, recover lost revenue, and protect their businesses through a unique success-based model. Backed by $49M from Viola Growth, OpenView, Sequoia Capital, and other top-tier global investors, Chargeflow is on a product-led growth journey. We’re a tight-knit team of passionate builders and entrepreneurs, united by our mission to revolutionize eCommerce and protect online businesses from chargeback fraud. What You’ll Own
* Lead, mentor, and develop a team of strong software engineers while remaining deeply involved in architecture and code.
* Own the architecture and evolution of Chargeflow’s AI platform.
* Design and build production-grade AI agents, intelligent workflows, and decision-making systems.
* Combine LLMs with business logic, company data, external tools, and deterministic software to solve complex product problems.
* Own AI systems throughout their lifecycle, from design and implementation to deployment, evaluation, monitoring, and continuous improvement.
* Make thoughtful architectural tradeoffs across accuracy, latency, scalability, reliability, security, and cost.
* Turn ambiguous product and business problems into clear technical direction, milestones, and measurable outcomes.
* Build evaluation frameworks that measure system quality, correctness, reliability, and business impact.
* Raise the bar for code quality, system design, observability, and engineering execution.
* Review designs and code, challenge assumptions, and help strong engineers become exceptional.
* Partner closely with Product, Data, and other R&D teams to turn emerging AI capabilities into meaningful customer value.
* Help define how engineering teams at Chargeflow build software with AI while maintaining high standards for correctness, security, and maintainability.

We are looking for a technically-grounded, visionary Product Owner to lead GenAI-powered initiatives within our B2B platform. You will stand at the intersection of cutting-edge LLM technology and enterprise-scale business impact, transforming how global financial institutions handle everything from underwriting automation to complex claims intelligence.

Key Responsibilities:
AI Roadmap & Strategy: Define and own the GenAI roadmap, identifying high-value use cases like fraud detection copilots, document intelligence, and agentic underwriting.
Backlog Excellence: Own and optimize the product backlog, translating complex AI concepts into clear user stories and acceptance criteria for engineering and data science teams.
Technical Specs & Orchestration: Read and write technical specs, API contracts, and data models. Youll work closely with Development & architecture teams
Experimental Mindset: Lead lean experiments and A/B tests to validate LLM performance, managing the balance between probabilistic AI outputs and deterministic business rules.
Stakeholder Leadership: Communicate the vision and progress transparently to global stakeholders and enterprise clients, acting as the bridge between "the possible" and "the practical".

We're looking for a Senior AI Solutions Builder to join our Product team. In this role, you will design, build, and ship AI-powered solutions that enhance productivity and drive measurable business value across the organization.

You will operate at the intersection of AI, data, pricing and business - owning the end-to-end development of agents, copilots, and workflow automations that directly inform decisions and eliminate manual work.

You are both a builder and an enabler. You ship solutions yourself and raise the AI capability floor for the teams around you. You'll collaborate closely with Product, Engineering, CS, Sales, and builders across the company to deliver outcomes that improve decision velocity, product and operational efficiency, and long-term growth.

You Will

Design and ship AI-powered copilots, agents, and decision-support tools for the Product team, starting with Pricing.

Build data pipelines and analytical models for pricing intelligence.

Develop autonomous agents that automate recurring Product tasks.

Automate manual workflows across product tools so the right action happens when a signal fires.

Build LLM-based scoring models that give roadmap and prioritization decisions a data backbone.

Enable and upskill product teams through AI playbooks, sessions, and hands-on co-building.

Collaborate with builders across Engineering, CS, GTM, and other teams to co-create solutions that scale.

Define and track impact: time-to-insight, decision velocity, manual hours eliminated, and business outcomes.

We are looking for a Senior AI Researcher to join our Research Group and help shape the future of intelligent media experiences at scale.

In this role, you will research and develop innovative AI-driven solutions for images and videos, explore emerging Generative AI technologies, train and adapt state-of-the-art models, and turn research ideas into scalable production-ready capabilities used by millions worldwide.

You will work closely with researchers, engineers, and product teams to identify opportunities where AI can create unique differentiators for us and deliver meaningful value to customers.

Responsibilities
Research and develop novel AI-based solutions for image and video understanding, generation, transformation, and optimization.

Explore and evaluate the latest advances in Generative AI and multimodal models, and identify practical applications for our products.

Train, fine-tune, evaluate, and optimize large-scale AI models and pipelines.

Design scalable approaches for serving AI models efficiently in production environments handling billions of assets.

Prototype new ideas rapidly and collaborate with engineering teams to bring research innovations into production.

Investigate opportunities to create proprietary models, unique workflows, and differentiated AI capabilities.

Stay up to date with the rapidly evolving AI ecosystem, including open-source and commercial foundation models.

Collaborate across research, engineering, and product teams to define future AI-driven experiences and capabilities.

Help shape the technical direction of our AI initiatives.

The company building an agentic development lifecycle, an infrastructure of autonomous agents that work alongside our engineers to accelerate and improve how we build software. Our goal is to ship faster, with higher quality, and to continuously tighten the feedback loop between what the agents produce and what engineering actually needs. Over time, this system should compound: every improvement makes the next one easier to reach.
we are an enterprise secure browser used by some of the largest organizations in the world. It's a complex, multidisciplinary product spanning browser core, frontend, extensions, and backend services, and it runs at scale for customers who need it to always work. The bar for what we ship is high. That means whatever agentic infrastructure we build has to meet the same standard. We're not here to vibe code our way to production.
We're looking for an AI Engineer with a product builder's mindset. You have real experience with AI and agentic workflows, and you know how to take a complex project from idea to adoption, technically and organizationally. That means working across teams, aligning with security, infrastructure, and other engineering groups, and understanding that building the system is only half the job. Getting people to trust it is the other half.
We aren't looking for a conventional senior developer; we need someone whose mindset is adapted to technical challenges that didn't even exist 18 months ago.

We are looking for a senior product manager to join our AI Unit and help shape the AI platform that powers next generation of products.

This role focuses on the platform and ecosystem layer of AI, building the capabilities, standards, and systems that enable teams across the company to create AI-powered experiences effectively.

You will work closely with engineering, data, and product teams to define how AI capabilities are built, reused, and governed across the platform.

This is a high-impact role with broad scope. It requires strong product fundamentals, technical curiosity, and the ability to operate in an evolving space.

We develop the AI infrastructure that powers the AI experience throughout the product. We ensure the production AI platform is stable, reliable and secure.
Our mission is not only to build AI-powered features, but to enable every product team to build reliable, scalable, and high-quality AI experiences.
We work with modern LLM technologies, agentic workflows, MCP, retrieval systems, evaluation pipelines, distributed systems, and production-grade AI infrastructure, deploying to production multiple times a day.
Job responsibilities
What You'll Do
As a Tech Lead, you'll play a key role in shaping the future of AI .
You'll combine deep technical expertise with strategic thinking, helping multiple teams build production-ready AI experiences while driving engineering excellence across the organization.
In this role you will:
Lead the technical direction of one of AI domains.
Design scalable AI architectures and production-ready agentic systems.
Drive technical decisions around LLMs, Retrieval, Tool Calling, MCP, evaluation frameworks, and AI infrastructure.
Own complex cross-team initiatives from design through production.
Collaborate closely with Product, Data, Infrastructure, and Engineering teams to turn AI opportunities into customer value.
Help define engineering standards and best practices for building reliable AI systems.
Drive engineering excellence through architecture reviews, mentoring, and technical leadership.
Balance rapid experimentation with production-grade quality and scalability.
Evaluate emerging AI technologies and identify opportunities to improve our platform and customer experience.

The Data Group builds and maintains the core data assets that power our products, from our Company and Contact databases to our Connect and Recommendation systems. The Data Tech Lead sits at the forefront of that mission, leading engineering innovation that directly shapes the experience of our growing user base and drives the evolution of intelligent data services.

This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

Your impact and responsibilities:

Leading the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
Defining, implementing, and enforcing engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
Mentoring, supporting, and growing a team of data engineers, fostering a collaborative and high-performance engineering culture.
Identifying opportunities to create new data assets and features that expand product capabilities and value proposition.
Driving architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
Collaborating closely with cross-functional stakeholders- including Product, DevOps, and R&D - to ensure effective delivery and platform stability.
Promoting and championing a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.

As an AI Product Owner & AI Process and Agentic Designer, you will own the process of transforming complex workflows into scalable AI solutions, bridging the gap between business stakeholders and AI Engineers. You will lead business process analysis, identify agentic process opportunities, validate business value, and define solution designs that enable successful AI implementation across the organization.

Responsibilities

Business Process Analysis & Discovery
Partner with business stakeholders to map, document, and analyze existing workflows, identifying inefficiencies, bottlenecks, and manual processes ripe for automation.
Conduct discovery sessions and workshops to deeply understand business needs, pain points, and success criteria across departments.
Agentic Opportunity Identification
Evaluate workflows to pinpoint where agentic and AI-driven approaches can deliver the most value, distinguishing tasks suited to automation, augmentation, or full agentic orchestration.
Maintain a prioritized pipeline of AI/agentic opportunities, assessing each for feasibility, complexity, and impact.
Business Value Validation
Define and quantify the expected business value of proposed solutions (e.g., cost savings, time reduction, quality improvement, revenue impact) and build the business case for investment.
Establish success metrics and KPIs, and track realized value post-implementation to ensure outcomes match projections.
Solution Design & Definition
Translate business requirements into clear solution designs, including agentic process flows, decision logic, data inputs/outputs, integration points, and human-in-the-loop checkpoints.
Define guardrails, escalation paths, and fallback behaviors to ensure solutions operate safely and reliably.
Stakeholder & Engineering Bridging
Serve as the primary liaison between business stakeholders and AI engineers, translating business intent into technical requirements and engineering constraints back into business terms.
Own the product backlog, prioritize features, and clearly communicate scope, trade-offs, and timelines to all parties.
Implementation Enablement & Iteration
Guide solutions through the full lifecycle from concept to deployment, supporting testing, validation, and change management.
Gather feedback, monitor performance, and drive continuous refinement of deployed AI and agentic solutions.
Scalability & Standardization
Identify reusable patterns, components, and best practices to scale successful solutions across the organization.
Contribute to governance frameworks, documentation standards, and design principles for AI/agentic product development.

we are seeking an experienced and visionary ML Engineer to join our dynamic technology organization. The successful candidate will be a part of a team of talented AI Engineers, Building agentic AI solutions, driving innovation and delivering business value through advanced Generative AI solutions & machine learning techniques. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge Gen AI and LLM methodologies and a passion for continuous learning and development.

Responsibilities

Build the solution: Own end-to-end technical delivery of agentic systems, from source-system integration through agent design, development, evaluation, and production deployment.
Integrate AI systems with source systems (Salesforce, Databricks, Splunk, internal APIs, business applications). Handle agent harness and orchestration.
Handle the operational handover to the business function and any necessary support transition.
Collaborate across teams: Partner closely with data engineering, platform, security, and business teams to align on requirements, dependencies, and integration points.
Engage stakeholders: Gather requirements directly from business functions, communicate technical trade-offs clearly, and keep stakeholders informed on progress, risks, and timelines.
Uphold quality and reliability: Establish and maintain best practices for code quality, testing, evaluation, monitoring, and observability of deployed AI systems.
Contribute to the team's technical growth through knowledge-sharing and help shape engineering standards and reusable patterns.
Stay current: Continuously evaluate emerging Gen AI, LLM, and agentic frameworks, and recommend tools and approaches that improve delivery speed and solution quality.

The role offers significant business impact, transforming complex challenges into scalable AI-powered products and solutions used in large-scale production environments. Key Responsibilities: Lead the end-to-end architecture, design, development, and deployment of advanced Generative AI applications, including Multi-Agent Systems and Retrieval-Augmented Generation (RAG) solutions. Design and optimize RAG pipelines, integrating Large Language Models (LLMs) with structured and unstructured data, including Knowledge Graphs and Vector Stores. Build, manage, and automate Generative AI solutions using AWS services, including Bedrock, S3, SageMaker, Lambda, and Step Functions. Lead Proof of Concepts (POCs) and evaluate emerging GenAI technologies and products to identify the most suitable solutions for business needs. Integrate AI solutions with existing enterprise systems using APIs and Microservices. Collaborate with data Engineers, Analysts, and Product Managers to translate business requirements into scalable and practical AI solutions. Implement advanced MLOps processes, including CI/CD, Docker, and monitoring solutions, to ensure the reliability, scalability, and maintainability of AI applications.

We are seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Code Generation and LLMs reasoning with specific focus on reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques. You will have the opportunity to work with a broad and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, resources, and research facilities.
AI Research Scientist Responsibilities
Lead, collaborate, and execute on research that pushes forward the state of the art in agentic code generation
Work towards long-term ambitious research goals, while identifying intermediate milestones
Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Mentor other team members. Play a significant role in healthy cross-functional collaboration.

Our Fundamental AI Research (FAIR) organization is seeking a Research Engineer to drive advancements in generative models. The role involves working across the full spectrum of research, engineering, and optimization for frontier model efforts.
Research Engineer, Fundamental AI Research (FAIR) - Generative Models/LLM Acceleration Responsibilities
Innovate, lead, and execute pioneering algorithmic research to push the state-of-the-art in generative models and LLM performance
Directly contribute to the experimental process, including designing details, implementing reusable code, running evaluations, and organizing results
Collaborate with cross-functional teams (research, product, infra) to build new and advance LLM optimization
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Lead initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Take a significant role in components, features, or systems with good end-to-end understanding
Contribute to publications, open-sourcing initiatives, and mentor other team members.

We are looking for a VP Data Intelligence & AI Enablement to join our Team.

Why is this role so important?

As VP of Data Intelligence & AI Enablement, you will own the data foundation that powers AI-native future.
You'll lead the BI team and the Data Analyst teams embedded in GTM (Sales, Marketing) and Product- teams that are already AI-fluent, working daily with Cursor, Git, and LLM tooling.
Your mandate is to channel that capability into building production-grade agentic solutions that drive measurable business outcomes across GTM, Product, and G&A.



So, what will you be doing all day?

AI Infrastructure (MCP): Develop the internal data and API layer to make business data accessible, safe, and actionable for AI agents across GTM and Product.

Proactive Intelligence: Shift the company from traditional reporting to automated, AI-pushed insights and dashboards delivered directly to stakeholders.

Semantic Layer & Governance: Build and own the unified semantic layer to ensure a single source of truth and eliminate metric misalignment across Sales, Marketing, CS, and Product.

Scaling Analytics with AI: Lead and upscale the data analysts function into "AI solution builders," implementing automated agentic workflows (using Cursor, Git, LLMs) to handle complex processes.

GTM & Product Analytics: Own the core analytical frameworks for key business metrics (Pipeline, Conversion, CARR, Retention, and Product Usage).

C-Suite Partnership: Serve as the strategic data thought-partner to the executive team (COO, CRO, CPO, CMO, CFO) to align data strategy with business priorities.