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Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

Were looking for a Product Lead to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

You will lead product vision and execution for critical capabilities that help organizations secure their AI systems end-to-end from data flows, to model governance, to AI usage in production. You will be accountable for turning complex customer problems into scalable product solutions, driving alignment across teams, and ensuring measurable customer and business outcomes.

This is a high-visibility, high-impact role with true ownership, where you will partner closely with Engineering, Design, Data, Security, and GTM teams to build a category-defining AI Security platform.


What Youll Do:
Own Product Strategy & Vision (End-to-End)
Define and own the product vision, strategy, and long-term roadmap for core AI security domains.
Make clear prioritization decisions based on customer value, business impact, and technical constraints.
Act as the product owner and decision-maker throughout the entire product lifecycle.

We are looking for an R&D Solutions Engineer to join the Agentic AI team within our companys AI for Security organization. This is a customer-facing role embedded directly within R&D, with a dotted-line relationship to the broader Solutions Engineering organization. You will work closely with R&D, Product, Sales, and SE teams to bring new Agentic AI capabilities into the hands of customers early, learn from real-world usage, and help turn emerging capabilities into products and sales motions that can scale.
You will report directly to the Director of Agentic AI within the AI for Security organization.
This is not a traditional presales SE role. Your primary focus will be building and managing relationships with design partners and Early Access (EA) customers, driving them toward meaningful product usage, and creating a tight feedback loop between customers and the teams building the product. You will also play a key role in taking capabilities that initially require direct R&D involvement and making them repeatable for the broader our company SE organization.
Key Responsibilities
What You'll Do
Own Design Partners and Early Access Customers
Identify and recruit strong candidates for design partnerships and Early Access programs, working closely with Sales and SE teams.
Own the technical relationship with design partners and EA customers from initial engagement through deployment and ongoing usage.
Build and maintain a healthy portfolio of actively engaged design partners.
Understand customers environments, workflows, security requirements, and success criteria.
Help customers deploy, configure, integrate, and evaluate emerging Agentic AI capabilities.
Drive customers toward meaningful real-world usage rather than isolated demos or proofs of concept.
Track adoption, outcomes, blockers, and feedback across the design partner and EA portfolio.
Maintain ongoing relationships with customers to ensure early enthusiasm turns into sustained engagement and actionable product feedback.
Bring the Field into R&D
Develop a deep understanding of how customers use the product and where they encounter friction.
Translate customer conversations into concrete product requirements, technical insights, and prioritization signals for R&D and Product.
Identify recurring patterns across customers rather than treating every request as a one-off.
Work directly with engineers and product leaders to reproduce issues, validate assumptions, and test potential solutions.
Regularly synthesize customer feedback into clear recommendations for R&D and Product.
Help the R&D organization understand what is required for new capabilities to succeed in real production environments.
Make New Capabilities Sellable and Repeatable.

As a Product Manager at Balance, you will own and evolve core product experiences that power how businesses manage and optimize their financial workflows. You will lead cross-functional initiatives across engineering, design, sales, and customer teams to deliver scalable, reliable, and intuitive solutions. As part of our evolution, you will help shape AI- and agent-driven workflows that redefine how financial operations are built and experienced. You will drive product initiatives end-to-end, identify new opportunities for growth, and ensure alignment with business goals and regulatory requirements.

Responsibilities
Own a core product domain, driving strategy, execution, and outcomes.
Collaborate with cross-functional teams including engineering, design, sales, and marketing to define requirements and deliver high-impact solutions.
Work closely with internal stakeholders and external partners to understand APIs, integrations, and system constraints.
Engage directly with customers and prospects to understand their workflows, validate solutions, and support enterprise conversations.
Translate complex business processes into simple, scalable, and user-friendly product experiences.
Define and ship AI-powered and agent-based product capabilities, both in customer-facing workflows and internal tooling.
Continuously monitor and improve product performance across both technical reliability and key business metrics.
Stay informed about industry trends, regulatory changes, and emerging technologies to identify new opportunities.

Were looking for a Senior Product Manager to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

You will define and drive the roadmap that helps organizations secure their AI systems end-to-end from data flows, to model governance, to AI usage in production. You will translate customer needs into actionable requirements, guide cross-functional execution, and ensure customers realize business value quickly and consistently.

This is a high-visibility, high-impact role where you will partner closely with Engineering, Design, Data, Security, and GTM teams to build a category-defining AI Security platform.

What Youll Do:
Drive Product Strategy & Roadmap
Define and own the product vision, roadmap, and priorities for core AI security workflows.
Translate market insights, customer feedback, and company goals into clear product direction.
Lead End-to-End Product Execution
Write crisp PRDs, use cases, and UX flows that bring clarity to complex technical problems.
Partner with engineering and design to ship features rapidly and iteratively.
Partner with Customers
Work closely with enterprise customers to understand risks, workflows, and success criteria.
Lead evaluations, POCs, and adoption programs to ensure customer value realization.
Enable AI Security Outcomes
Drive the development of capabilities across data protection, AI governance, observability, and secure AI operations.
Align product decisions with emerging standards, compliance requirements, and threat models.
Collaborate with GTM teams on packaging, messaging, and enablement.
Communicate roadmap, timelines, and impact to internal and external stakeholders.

We are looking for a Senior Software Engineer to join the AI Engineering team in a role focused on embedding directly with business teams to drive AI transformation. Be at the forefront of Applied AI. This role is outward-facing: you will engage with GTM and G&A functions - Sales, Marketing, Finance, HR, Legal, Customer Success - and fundamentally alter how these teams operate with AI.

What you will be doing:
Embed with GTM and G&A teams (Sales, Marketing, Finance, HR, Legal, Procurement, Customer Success) to identify, scope, and prioritize the highest-impact AI opportunities within each function, and act as both product manager and engineer for these initiatives.
Own the full lifecycle of each solution, from requirements gathering through deployment to adoption measurement and iteration, with a focus on business outcomes.
Serve as the primary technical partner and AI advisor for business function leaders, translating their needs into engineering plans and helping them develop their own AI fluency.
Develop and deliver hands-on AI enablement and training for non-R&D teams, building their ability to use AI tools independently and effectively.
Collaborate with the team to leverage shared infrastructure (MCP servers, RAG systems, evaluation frameworks, guardrails) while feeding back requirements from the field.
Measure and report on AI adoption impact - unlocking new opportunities, process improvements, and capability gains - to build the case for continued investment and to guide prioritization.

our company's product does the work a SecOps engineer does: it investigates coverage gaps against live enterprise security data, authors and tests detection logic, and tunes noisy alerting. That means product decisions here are SecOps engineering decisions, and they need someone who has actually done the job. You'll join our company's product team and own the detection engineering surface of the product - what good coverage analysis looks like, what correct detection content looks like, what a security team should be able to trust the product to do on its own. we are defining a category around Security Operations Resilience, and the fastest way to get that right is to be genuinely credible with the SecOps engineers we're building for.
What you'll be doing
Drive the detection product domain: Bring deep expertise in SecOps engineering across SIEM, data pipelines, and SOAR, and help the product team define where the product should excel. Develop a strong understanding of the day-to-day work of SecOps engineers and the challenges they face.
Turn expertise into product insight: Conduct deep, hands-on research across real security environments, SecOps engineering practices, data, and tooling. Combine customer feedback with your own experience and the knowledge of the broader team to identify meaningful problems, opportunities, and product directions.
Shape and execute the roadmap: Translate product insights into a focused roadmap aligned with company strategy and customer needs. Partner with the product and engineering teams to prioritize initiatives, make tradeoffs, define outcomes, and drive execution from discovery through delivery.
Turn problems into product direction: Translate ambiguous problems into clear product requirements and actionable plans. Work closely with engineering, design, and security experts to ensure complex technical problems are translated into products that are useful, intuitive, and technically sound.
Shape and evaluate AI agent capabilities: Define what our companys AI agent should be capable of doing as a SecOps engineer, what good looks like, and where it must be trusted or constrained. Develop evaluation frameworks, scenarios, and ground truth to measure and continuously improve agent performance.
Own product quality and outcomes: Maintain a deep understanding of how the product is used in real-world security operations. Validate assumptions, identify gaps, and use customer feedback, product data, and operational experience to continuously improve the product and its direction.

Were looking for a hands-on AI Solutions Manager who combines deep practical knowledge of generative AI tools with strong business understanding. This role sits at the intersection of technology and impact - identifying real organizational needs and translating them into scalable, AI-driven solutions.

This role is perfect for someone who lives and breathes AI technology, stays ahead of the rapidly evolving landscape, and knows how to turn cutting-edge capabilities into real-world solutions.

What Youll Do

Collaborate with cross-functional teams to identify opportunities where AI can solve complex business and internal problems
Evaluate and select the right AI tools and models (Claude, Gemini, OpenAI, etc.) based on use case, limitations, cost, performance, and scalability
Design and implement AI-powered solutions and internal automations using LLM APIs and workflow platforms (e.g., N8N, Workato)
Build and optimize prompts, RAG pipelines, and AI agents while understanding model limitations and trade-offs
Architect scalable AI workflows and integrations across systems (e.g., Salesforce, Jira, Confluence, , etc.)
Lead hands-on projects from ideation to rollout, iterating rapidly to deliver value
Stay up to date with emerging AI capabilities and continuously evaluate new tools and frameworks
Educate and guide the organization how to adopt and use wisely AI tools and models

As a PM here, you own one of those systems end to end: you set the strategy, work daily with a team of engineers and data scientists in Tel Aviv, and drive decisions that show up in company-level growth numbers. The problems are genuinely hard and mostly unsolved - how do you prove the value of a channel you can't fully instrument, how do you respond to an ecosystem highly disrupted by AI, how do you make someone want an app before you ask them to sign up.
Product Manager, Central Products Responsibilities
Is the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals
Generate buy-in and drive consensus across organizations. Bring clarity and structure to ambiguous opportunities. Consistently demonstrate initiative and execute with limited oversight
Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis
Translate AI capabilities into compelling, differentiated product visions that define market categories
Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement
Drive product development with teams of engineers and designers, while maintaining team health
Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones
Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale
Foster a culture of rapid experimentation and learning that becomes a competitive advantage
Scale AI best practices (including responsible AI use), workflows, and artifacts across the organization so capability compounds exponentially
Plan, initiate, and manage information technology projects for web-based products, applications, and platforms
Orchestrate complex execution across multiple organizations by combining AI automation with strategic human oversight at scale
Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm
Use AI-enabled tools to build products-setting the standard for PM technical capability
Interpret research and state-of-the-art learnings to design product strategy and apply rigorous logical reasoning at the frontier
Demonstrate expert understanding of system/architecture trade-offs and how they impact user experience and business outcomes; lead strategic technical decisions with engineering leadership
Integrate data, usability studies, research, and market analysis into product strategies and requirements to enhance user satisfaction and improve engineer productivity
Express complex and technical concepts at the right altitude, choosing the right medium and level of detail for the audience (XFN partners, execs, engineering, etc.)
Understand Meta's strategic and competitive position and deliver products that are aligned with our mission and recognized best in the industry
Define and analyze metrics that inform the success of products. Identify and track key performance metrics. Drive decision-making through user insights, quantitative analysis, and AB testing
Design sophisticated experiments and interpret results (leveraging AI) to drive strategic product decisions
Define and run evaluations (evals) to interpret model outputs at scale-establishing evaluation as a strategic capability for AI-powered experiences