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We are seeking a highly skilled and analytical Senior Data Engineer to join our Data team. In this role, you will design and implement robust data pipelines, while uniquely bridging the gap between engineering and analytics by actively analyzing data to extract actionable insights. You will play a crucial part in architecting our data foundations to support everything from business intelligence to advanced machine learning and agentic AI pipelines.
As a Senior Data Engineer, you will collaborate closely with engineering teams, product managers, and stakeholders across the organization. You will not only build the infrastructure utilizing modern data stack tools but also act as a data analyst when needed, ensuring our systems are fully equipped to operate within and support a cutting-edge agentic AI environment.
Responsibilities
Design, build, and maintain highly scalable ELT/ETL data pipelines.
Architect and manage modern cloud data warehousing solutions.
Develop, maintain, and monitor Python services responsible for robust data collection and ingestion.
Perform hands-on data analysis to interpret complex datasets, identify trends, and deliver business insights, acting in a dual capacity as a Data Analyst.
Develop and optimize data infrastructure specifically designed to support autonomous agentic workflows and LLM integrations.
Collaborate with engineers and analysts to troubleshoot data issues, enforce quality SLAs, and define data requirements.
Document data architecture, flow, and analytics standards for internal team alignment.
Build and maintain dashboards and reports to communicate analytical findings and data health to the organization.
Maintain Kafka consumer applications that process high-volume event streams in real-time, ensuring reliable ingestion into cloud databases.

our office in Israel is seeking an Architect to join our growing team.
This is an opportunity to be part of a collaborative, innovative environment, delivering world-class design solutions for leading global clients.
we design some of the most complex and specialized facilities in the world-including semiconductor manufacturing plants, data centres, and other advanced technology environments. If youre motivated by technically challenging projects and enjoy working in a dynamic, multi-disciplinary setting, wed love to hear from you.
Key responsibilities include:
Lead and coordinate architectural design activities within a defined project scope, working closely with multi-disciplinary engineering teams
Deliver architectural design solutions using 2D and 3D integrated design platforms
Perform quality reviews of models and architectural deliverables to ensure accuracy and compliance
Participate in design reviews, risk assessments, and vendor evaluations
Support the preparation of effort estimates and design deliverables for the architectural discipline
Contribute across all project phases, including concept design, master planning, design development, and construction support
Collaborate effectively in a fast-paced, deadline-driven environment

We are seeking an experienced and passionate Senior Software Engineer to join our core engineering team. In this role, you will design, build, and scale high-performance backend services that power our enterprise Agentic AI platform. You will tackle complex technical challenges, architect robust systems, and work on cutting-edge features that seamlessly integrate AI agents into enterprise workflows.
As a Senior Software Engineer at our company, you will collaborate closely with product managers, and cross-functional engineering teams. You will take full ownership of end-to-end feature delivery from initial system design and API definition to production monitoring and optimization - ensuring our platform maintains top-tier reliability, security, and execution velocity.
Responsibilities
Design, architect, and maintain highly scalable, high-throughput backend services and distributed systems.
Take end-to-end ownership of features and projects, driving them from technical design through to deployment and monitoring.
Build and optimize core APIs and integration layers.
Write clean, testable, and maintainable code, adhering to software engineering best practices (CI/CD, code reviews, automated testing).
Drive architectural decisions, lead technical design discussions, and advocate for system performance and scalability improvements.
Troubleshoot and resolve complex production issues, ensuring high system availability and low latency.
Mentor and guide junior and mid-level software engineers, driving engineering excellence across the team.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

We're looking for an AI Growth Marketing Lead to build the demand engine for our Agentic HR platform from the ground up. We're creating a new category, and you'll define what an AI-native growth motion actually looks like: not by directing it, but by building it yourself with the best tools available, and owning the pipeline number it generates.
In your day-to-day, you'll run the full path across our mid-market and enterprise motions - paid, organic, content, email, webinars, ABM, events, and executive roundtables - while designing and shipping the AI-powered workflows that make it all run: intent-triggered outbound in Clay, agents in Claude and n8n, pages and campaigns you spin up yourself instead of waiting on anyone. You'll work closely with Sales, Alliances, and Product, and have unusual latitude to test, ship, and scale what works.
One thing to be clear about: this is not a marketing ops or tools-configuration role. The tools are your leverage. Marketing judgment, including knowing what moves an enterprise buyer, what a healthy funnel costs, and which experiments deserve to live, is the job.
Responsibilities
In this role you'll
Own the pipeline generation number and the growth strategy behind it: targets, channel mix, budget allocation, and the experimental framework to hit them
Design and run the full demand generation mix, tuned to the different rhythms of mid-market and enterprise buying cycles
Build the AI-native motions displacing traditional spend: intent-triggered outbound, AEO/GEO, signal-based plays, and agent-run workflows that work while you sleep
Run a disciplined test-and-iterate loop across channels, messaging, offers, and audiences - compounding what works, cutting what doesn't
Design, build, and maintain the workflows that run the growth motion, hands-on in Clay, Claude, n8n, Qualified, HubSpot, and Salesforce, and continually adopting what's next
Define the metrics that matter, build the reporting cadence, and present pipeline performance and spend efficiency to leadership
Work shoulder-to-shoulder with our C-suite to build and scale our growth engine - no layers, no red tape. Your growth experiments shape company strategy from day one
Partner with sales and product to keep messaging tight and conversion high at every touchpoint.

You'll own a core part of the platform end to end - from the primitives our customers build on to the experience of configuring and running agents inside a live enterprise. You'll have a lot of ownership while staying in the details day to day.
You'll succeed here if:
You build and work with AI tools yourself and can speak concretely about where they're strong and where they break.
You think in systems and data models, not screens - you get why the underlying record and data matters more than the UI on top of it.
You have real opinions about how agents should behave in production, and the judgment to know when a slick demo won't survive contact with a real customer.
You move fast, make tradeoffs explicit, and are comfortable making informed calls without perfect information.
Responsibilities
What you'll do
Own product areas from discovery to launch. Run the research, make the calls, ship the thing.
Own the primitives agents are built from - how they get context, which tools and systems they can act on, how work moves between them, and where a human stays in the loop. You're designing the composable layer, not one-off agents.
Build for extensibility. The people configuring agents on this platform are our customers, so the connectors, configuration, and guardrails have to hold up in hands you've never met.
Design how agents behave, what they know, what they're allowed to do, when they act, and when they hand off to a human.
Prototype your own ideas. Show, don't tell: stand up a working demo before it eats engineering time.
Sit close to customers (CHROs, HRIT, HR leaders), and turn what you hear into product decisions.
Make the hard calls on scope and sequencing, including what not to build.