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Requirements:
5 to 9 years shipping production software, with at least one seed to Series B stint where you owned a system end to end rather than a ticket queue.
Full-stack breadth over narrow depth. Modern TypeScript, React, Node, and a major cloud with containers. You are AI-native: you build, test, and ship with AI coding and agents, and stay in control of what you ship.
You scope your own work and have shipped where real users or revenue were on the line. Resume tell: employee #2 to #10 somewhere, "built X from scratch."
You can hold a conversation with hospital IT without hiding behind jargon.
Nice to have
Healthcare or health-tech exposure.
ML, data-pipeline, or model-monitoring experience.
Prior early-hire or founding-engineer experience.

Requirements:
- 6+ years in integration, automation, or enterprise software roles.
- Deep hands-on with Priority ERP (or SAP B1 / NetSuite) - workflows, APIs, data model.
- Strong experience with iPaaS platforms - our company, Workato, MuleSoft, Boomi, Make, Zapier, n8n.
- Fluent with REST APIs, webhooks, OAuth, SQL; comfortable reading OpenAPI specs cold.
- You've built an automation that processes thousands of transactions a day and rarely breaks.
Nice to Have
- Experience with OCR pipelines (Tesseract, Textract, OpenAI Vision).
- Israeli market ERP fluency (Priority, חשבשבת, Rivhit, Icount).
- Exposure to AI-Worker / agentic patterns.

Requirements:
What Makes You Successful:

You combine technical excellence, commercial thinking, and leadership capability.

Technical Expertise:
Experience in one or more of the following domains: SIGINT, telecommunications, cybersecurity, intelligence systems, RF technologies, big data, analytics, WEBINT, data fusion, AI/ML, cloud, or enterprise software platforms.

Business & Leadership Skills:
Strong customer and commercial orientation.
Ability to architect innovative and commercially viable solutions.
Proven ability to lead without authority and drive cross-functional initiatives.
Excellent project management and organizational skills.
Ability to solve complex problems.

Communication Skills:
Native-level English proficiency, written and verbal.
Exceptional writing, presentation, and storytelling capabilities.
Ability to communicate effectively with customers, internal stakeholders, executives, and senior management.

Preferred Qualifications:
Experience in presales, solution architecture, consulting, system engineering, product management, or customer-facing technical leadership roles.
Experience leading complex RFI/RFP submissions.
Experience working with intelligence, defense, government, telecommunications, cybersecurity, or enterprise customers.
B.Sc. in Computer Science, Electrical Engineering, Information Systems, Telecommunications, or related field.

Requirements:
What You Bring
- 4+ years shipping production frontends on complex SaaS products.
- Expert React + TypeScript. Comfortable with modern state (Zustand, Jotai, TanStack Query, Redux Toolkit).
- Strong CSS craft - Tailwind, CSS-in-JS, design tokens, responsive and dense layouts.
- Experience with visual/canvas-heavy UIs - React Flow, XYFlow, d3, custom canvas/SVG.
- You care about UX the way a backend engineer cares about p99 latency.
Nice to Have
- Next.js (App Router), server components, streaming, Suspense.
- Realtime stacks (WebSockets, WebRTC, Yjs, Liveblocks).
- Experience building workflow/automation/no-code builders (Zapier, Make, n8n, Retool, Airtable, Monday).
- Open-source contributions.

Requirements:
- 4+ years of ML engineering in production (not just research or notebooks).
- Hands-on LLM experience in 2025-2026: agentic systems, tool-use, function-calling, RAG, structured output, eval design.
- Strong Python. Comfortable with PyTorch/JAX and one serving stack (vLLM, TGI, TensorRT-LLM, SageMaker, or similar).
- You've built an eval pipeline that actually caught a regression in prod.
- You read the papers and know which ones to ignore.
Nice to Have
- Experience with MCP, LangGraph, DSPy, or custom agent frameworks.
- Fine-tuning (LoRA/QLoRA, DPO/ORPO, RLAIF) on open-weight models (Llama, Qwen, Mistral, DeepSeek).
- Vector DBs (pgvector, Pinecone, Weaviate, Qdrant), reranking, hybrid retrieval.
- Prior work on multi-agent systems or enterprise copilots.

Requirements:
- 5+ years as a Solutions Architect, Pre-Sales Engineer, or Integration Architect in B2B SaaS / iPaaS / enterprise software.
- Deep hands-on experience with at least 2 ERP/CRM ecosystems - Priority, SAP (S/4HANA or B1), NetSuite, Salesforce, HubSpot, Dynamics, or Monday.
- Strong API fluency - REST, GraphQL, webhooks, OAuth, SSO/SAML, event-driven patterns.
- You can design a system on a whiteboard and defend it against a skeptical enterprise architect.
- Excellent English + Hebrew, customer-facing presence, executive communication.
Nice to Have
- Experience with iPaaS platforms (Workato, MuleSoft, Boomi, Zapier, Make, n8n).
- Exposure to MCP, LangChain, agent frameworks, or LLM-powered automation.
- Background in manufacturing, logistics, financial services, or Israeli market ERPs.
- Technical writing or public speaking experience.

Requirements:
5+ years experience as presale/solution engineer in a global technology company.
Proven experience in selling software solutions to organizations in the law enforcement, intelligence, defense or national security domains.
Familiarity with multi‑source data fusion and analytics platforms, including exposure to investigative workflows and AI or machine‑learning driven analytics.
Ability to work independently as customers technical/presale key focal point, while promoting company goals.
A proficient public speaker with the ability to deliver the message clearly to a technical audience and C-level executives alike.
The position requires frequent travel (up to 25% of the time).
Excellent English communication and presentation skills. Other languages - French, Russian, Spanish - big advantage.
Previous experience as an analyst, investigator, or operational intelligence user - big advantage.

Requirements:
M.Sc. or higher in Computer Science, Mathematics, Engineering, or a related quantitative field.
7+ years of hands-on experience building and deploying ML/AI solutions in production, including 2+ years leading or growing a data science/ML team.
Proven experience designing and shipping GenAI-based product features and multi-agent systems using modern orchestration frameworks such as LangGraph, CrewAI, or AutoGen, including RAG, vector databases, and tool/function calling.
Practical experience with the agentic production stack: observability/eval tooling (e.g., Langfuse), durable workflow orchestration, and typed service design.
Strong foundation in classical machine learning - supervised/unsupervised methods, feature engineering, model evaluation - and sound judgment for when to use classical models over LLMs.
Advantage: Demonstrated experience fine-tuning and deploying small/large language models, including SFT and preference/RL-based methods such as GRPO or DPO.
Advantage: Experience with model optimization and efficient serving: quantization, pruning, LoRA/QLoRA, and high-throughput inference frameworks such as vLLM.
Advantage: Experience designing end-to-end ML pipelines (versioning, training/tuning, deployment, testing, monitoring) on cloud-native infrastructure (Kubernetes, GCP/AWS).