--- title: 'Staff Backend Engineer (Full Stack), Context Management at Wand Synthesis AI Inc' canonical: 'https://feeny.ai/job/staff-backend-engineer-full-stack-context-management-wand-synthesis-ai-inc-tjx1k9fgg6xv' type: 'job' last_seen: '2026-09-07' --- # Staff Backend Engineer (Full Stack), Context Management at Wand Synthesis AI Inc - **Company:** Wand Synthesis AI Inc - **Location:** Europe - **Employment:** full-time - **Work type:** remote - **Posted:** 2026-05-22 - **Last confirmed live:** 2026-09-07 - **Apply:** https://jobs.ashbyhq.com/wand-ai/cd4554b5-9242-4ea2-a492-3849d040b670/application **Skills:** Python, FastAPI, BlackSheep, Temporal, Elasticsearch, MongoDB, PostgreSQL, Redis, ClickHouse, Snowflake, OpenAI, LangChain, LangGraph, LiteLLM, Docling, RabbitMQ, Kafka, Azure, Docker, Kubernetes > Design and build scalable search, retrieval, and context management systems for AI agents. Own the full lifecycle of data pipelines and integrations with enterprise sources, optimizing for latency and relevance in a high-paced startup environment. ## Job description Build the Future Workforce Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. And it’s already operating at scale inside some of the world’s largest organizations. Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces. Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy. We’re building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale. Join Wand in leading the Agentic Shift Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers. You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern. Position Summary: This role is ideal for a hands-on staff-level engineer with 10+ years of experience who is primarily a strong backend engineer but is also competent across the frontend. This is a full-stack, product-focused role (roughly 60% backend, 40% frontend) building the dashboard and connector-management product: the control panel for connectors, metrics, and dashboards that powers our AI agents. Most of the work is on the backend, with the frontend building enterprise-grade UIs in close collaboration with designers. You will own a part of the roadmap end-to-end, organize the work, split it across the team, and take ownership of delivery. Toward the end of the year, more agent capabilities will be folded into this product, including agents that build connectors themselves. Our tech stack includes: - Backend: Python, FastAPI, BlackSheep, Temporal - Data & Search: Elasticsearch, MongoDB, PostgreSQL, Redis, ClickHouse, Snowflake - AI/ML: OpenAI, LangChain, LangGraph, LiteLLM, Docling - Messaging: RabbitMQ, Kafka - Cloud & Infra: Azure, Docker, Kubernetes Responsibilities: - Design and build the dashboard and connector-management product end-to-end, including the control panel for connectors, metrics, and dashboards. - Build enterprise-grade UIs on a modern frontend stack (React preferred), working closely with designers to turn client requirements into polished, usable interfaces. - Own part of the roadmap: organize the work, split it across the team, and take ownership of delivery. - Develop and maintain connectors to enterprise data sources (SaaS platforms, data warehouses, document stores, APIs). - Build data pipelines that ingest, transform, and index customer data for use by AI agents. - Integrate with LLM providers and related frameworks (e.g., LangChain, LlamaIndex) to deliver context-aware agent capabilities. - Pull and process analytics data from customers' warehouses (Snowflake, BigQuery, Databricks, etc.). - Own projects end-to-end: from architecture and technical design through implementation, deployment, and ongoing maintenance. - Collaborate with product and AI teams to translate retrieval quality into measurable agent performance improvements. - Optimize retrieval pipelines for latency, relevance, and cost efficiency at scale. - Uphold a culture of high efficiency, creativity, and quality. Key Qualifications: - Degree in Computer Science, Engineering, or a related field. - 10+ years of engineering experience - Strong proficiency in Python; willingness to work in additional languages as the stack evolves. - Experience delivering enterprise UI projects. - Experience with a modern frontend stack (React preferred). - Comfortable owning a part of a roadmap and organizing and splitting work across a team. - Proficiency in at least one cloud environment (GCP, AWS, Azure). - Proven track record in a high-paced startup environment. - Self-sufficiency across the stack, comfortable operating without dedicated DevOps support. - Experience with containerized environments (Docker, Kubernetes). Preferred Experience: - Background in building enterprise SaaS integrations or source connectors at scale. - Background working on enterprise configurations, features, dashboards, or a developer platform (e.g., at a company like Miro), spanning client requirements, UI, and backend. - Experience with RAG (retrieval-augmented generation). - Experience building AI agents. - Hands-on experience with search technologies (Elasticsearch, vector databases such as Pinecone, Weaviate, Qdrant, or similar). - Solid understanding of embeddings, semantic search, and retrieval-augmented generation (RAG) patterns. - Experience building and maintaining data pipelines and ETL/ELT workflows. - Familiarity with at least one major data warehouse platform (Snowflake, BigQuery, Databricks, Redshift). - Experience working with LLM APIs and agent frameworks in production. - Experience with chunking strategies, re-ranking models, and hybrid retrieval approaches. - Experience on search, information retrieval, or data engineering. - Familiarity with data governance, access control, and multi-tenant data architectures. - Contributions to open-source search or retrieval projects. - Experience with production systems serving enterprise customers. Personal Characteristics: - Strong individual contributor comfortable owning major projects with minimal oversight. - Thinks architecturally: balances long-term design quality with startup speed. - Excellent communication and interpersonal skills. - Continuous drive for improvement and innovation. ## About Wand Synthesis AI Inc ## Company Overview - **One-liner**: Wand AI builds the world’s first Agentic Labor Infrastructure, an operating system that enables governments and global enterprises to create, manage, and scale hybrid workforces where humans and AI agents collaborate seamlessly. - **Entity Type**: Private (Seed stage; $15M total funding) - **Headquarters**: Palo Alto, California, United States (also operates from Tel Aviv, Israel) - **Founded**: 2022 - **Founders**: Rotem Alaluf (CEO), Eli Osherovich (Co-Founder) ## Core Business - **Primary industry/industries**: Enterprise AI Infrastructure, Agentic Automation, Workforce Management - **Target customers**: Governments and global enterprises (B2B, Enterprise) - **Mission or purpose statement**: “To drive a generational leap for the global economy by integrating agent ecosystems into the core of work, business, and society — making this shift safe, transparent, and radically efficient.” ## Products & Services - **Agent Control Panel**: Configure, monitor, and govern every AI agent with live performance data, budget restrictions, and compliance controls. - **Collaboration Platform**: A shared chat workspace where humans prompt, collaborate with, and coach AI agents in real-time. - **Process Automation**: Agents run complex workflows end-to-end, triggering tasks and escalating edge cases to humans. - **Division Automation**: Hand an entire function (e.g., customer support, data operations) to AI when the business is ready, scaling from single processes to fully autonomous divisions. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: $15.0M in total funding across 2 rounds - **Notable Investors/Partners**: InnoRevo Ventures (lead investor in seed round); backed by world-renowned entrepreneurs and leading U.S.-based venture capital firms. Acquired Accern (2025-02-07). - **Growth Signals**: - Headcount of 48 employees (+5.8% YoY), operating in 13 countries - 21 active job postings (monthly job postings up +200%) - LinkedIn followers: 113,174 (monthly +0.1%, yearly +1.6%) - Talent sourced from Amazon Web Services, Microsoft, IBM, Jasper, and others - SOC2-ready with flexible deployment (on-premise, private cloud, hosted) ## Competitive Advantages - **Full-Stack Workforce OS**: One platform for creation, execution, collaboration, and governance — unlike point solutions that only automate tasks. - **Governed Autonomy**: Agents stay budget-positive and compliant under built-in rules and guardrails, with decision tracking and accountability dashboards. - **Human-First Adoption**: Real-time chat, clear escalation paths, and role-based controls keep people in command. - **Self-Evolving Intelligence**: Agents retrain, build new agents, and refine workflows automatically, compounding ROI over time. - **Interoperability**: Agents work across systems, tools, and departments, eliminating silos and enabling unified operations. ## Strategic Focus - **Category creation**: Defining the “Agentic Labor Infrastructure” category and becoming the company the world thinks of first for using AI to create real business value. - **Scaling the hybrid workforce**: Enabling enterprises to move from single-process automation to full-division autonomy. - **Global expansion**: Operating in 13 countries with a growing presence in Middle East, Europe, and Asia. - **Talent acquisition**: Aggressively hiring across engineering, product, go-to-market, and marketing to build foundational infrastructure at the frontier of AI. ## Why Work Here - **Culture highlights**: “Real ownership from day one” and “the chance to help define a category, not iterate inside one.” The team includes talent from DeepMind, Google Brain, Microsoft Research, and other industry leaders. - **Remote/hybrid/office policy**: Not explicitly stated, but the company operates across 13 countries with employees in the US, India, UAE, Israel, Ukraine, Poland, Netherlands, Denmark, Switzerland, Germany, and more — suggesting a distributed/remote-friendly model. - **Notable perks or engineering culture**: - Employer rating: 3.7/5.0 (13 reviews) — Compensation rated 3.9, Career growth rated 3.9 - Work on foundational infrastructure at the frontier of AI (agent runtime, orchestration layer, customer-facing products) - SOC2-ready security posture and enterprise-grade deployment options - Opportunity to work on a product that “will change how organizations everywhere operate” - **Open roles include**: Head of Product Security & Compliance, Head of Engineering (Organization & Governance), Senior Backend Engineer, Senior ML Engineer, Senior Site Reliability Engineer, Customer Solutions Engineer, Engineering Manager (Full Stack/Frontend), and more. ## Sources 1. [wand.ai](https://wand.ai/) 2. [wand.ai/careers](https://wand.ai/careers) 3. [LinkedIn - Wand AI](https://www.linkedin.com/company/wand1) 4. [wand.ai - Meet Wand: What We Build, Why It Matters](https://wand.ai/blog-old2/meet-wand-what-we-build-why-it-matters) 5. 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