דרושים » תוכנה » Senior AI Engineer - Marketing AI Transformation

we are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

we are looking for a AI Transformation Engineer.
You'll join the AI Platform team, the group building the AI infrastructure, agentic workflows, and tooling that power R&D organization. Our mandate is to make the entire software development lifecycle faster and smarter with AI, and we're a small, hands-on team that ships real systems, not pilots
This isn't a role where work arrives as tickets, and it isn't a prompt-engineering role. You'll own a set of KPIs the team is driving, and it's on you to turn a fuzzy goal into something measurable: figure out what actually needs to be built, define how you'll know it's working, and build it. That means talking to engineers, understanding where the SDLC breaks down, and turning that into agentic workflows and platform capability that ship and hold up over time.

our company's product is built around an AI agent that security analysts and detection engineers work with directly. It investigates coverage questions against live enterprise security data, authors and tests detection logic, and tunes noisy alerting.
That agent is already in production with enterprise design partners. Now we need to make it dependable and scalable enough for GA.
You will own that evolution: the agent architecture, its evaluation and quality system, and the production engineering around it. This is a hands-on senior IC role with real architectural authority - you set the technical direction and you write the code.
The agent operates inside customer security environments, where a wrong action can become a customer incident. Correctness, isolation, observability, and evaluation are not polish. They are the product.
What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.

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.

Security teams are not short on tools. They are short on time, alignment, and the ability to actually close exposure. That's why most breaches could have been prevented with a tool that was already in use.
our company was built to change that.
We are the first Agentic Exposure Ops Platform, designed to prevent the preventable breach by turning fragmented signals into coordinated action. Our agents investigate risk, drive remediation, and verify that issues stay closed, continuously, without adding overhead.
we are helping organizations move from reactive workflows to continuous execution, replacing manual effort with systems that actually move the work forward.
At our company, engineering isn't a service function it's where product happens. We're looking for a Fullstack (Product) Engineer who lives at the intersection of craft and product sense:You care as much about why we're building something as how it feels in the user's hands. You're an engineer who connects naturally with other engineers, and who enjoys mentoring and ramping up the people around you.
You'll own experiences end-to-end from the first PRD conversation to the KPI dashboard weeks after ship. You'll shape our component library, raise the bar on our frontend infra, and help define what "good" looks like across the R&D org. This isn't a role where you get handed pixel-perfect mocks and a closed ticket. You'll have opinions, and we'll want to hear them.
What you'll do
Craft the experience. Design and build polished, performant UI in Vue 3 (Composition API) from the tiny interaction details to the data layer behind them.
Own the full journey of a feature. Partner with Product on the PRD, define the KPIs that actually matter, ship it, then track whether it moved the needle and iterate honestly if it didn't.
Shape the component library. Evolve our patterns, primitives, and the infra that lets the whole team build faster without sacrificing quality or consistency.
Go full-stack when it counts. Write Node (NestJS) services and work across our data stack (Postgres, Snowflake, ClickHouse) to deliver features truly end-to-end.
Push AI-assisted development forward. Build the guardrails, skills, and workflows that let engineers contribute code quickly and safely you'll help make AI a force multiplier for the whole team, not a liability.
Raise the bar org-wide. Your taste in UX, and code quality should ripple well beyond your own team.

We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.

What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

we are looking for a Senior AI Builder to take AI from a "promising demo" to real production systems that customers rely on - and that continue to work well over time. Our R&D group is a team of 12 engineers and one architect, spanning backend to mobile, building the accounting platform businesses actually run on every day.
What you'll do
* Build and ship LLM-powered AI capabilities to production- agentic flows, retrieval over our data, extraction from real-world documents, and more. Solutions need to be accurate, measurable, cost-efficient, and rollback-ready.
* Build and lead the evaluation process - continuously measure the quality of models and solutions, and be able to answer clearly: is the new version actually better than last week's?
* Own whatever it takes to get the solution into production- from AWS Lambda to Vue and PHP. You don't need to be an expert in every technology, but you should be comfortable getting into the code and solving problems wherever the work actually lives.
Why this is a real challenge - and why it's worth it Our customers trust us with their financial data. There's no room for "almost right" when it comes to the answers our systems provide, and we operate in an environment with significant regulatory requirements- including PCI-DSS, GDPR, and Israeli privacy law. The goal is to take AI capabilities, turn them into real products people can trust, and see them reach customers- at a company small enough that your work can ship this quarter, not next year.
Advantages:

* Experience with Databricks/Spark, Vue 3, fintech or another regulated domain, and significant experience with AI-powered development tools and agentic development.

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.