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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Architect (UA/RU Language speaking) - **Company:** Neurons Lab - **Location:** Spain (Remote available) - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Governance, Python (Programming Language), Machine Learning, Neo4j, Role-Based Access Control, Systems Architecture, Microsoft Power Automate, Large Language Models, Model Validation, Amazon Virtual Private Cloud (VPC), Data Layers, Hubspot - **Published:** August 4, 2026 - **Apply:** https://es.indeed.com/viewjob?jk=18b53620742cc172 ## About the Role * Agentic system architecture end to end: retrieval, tools, orchestration, memory, evals, guardrails * Ontology / knowledge-graph engineering and semantic layers over heterogeneous sources (RDF/OWL, Neo4j, dbt-style modelling - pragmatism over purity) * RAG / GraphRAG at production quality, including hybrid retrieval and permission-aware retrieval * MCP, tool-calling and connector platforms; designing agents that perform actions with side effects safely * Private / sovereign deployment: VPC, on-prem, self-hosted or open-weight models; AWS and/or GCP data + AI stack * Identity, access control and data governance applied to AI systems (RBAC/ABAC, scoping, audit) * Strong hands-on Python; comfortable writing the hard 20% of the code yourself * Evals & observability for LLM systems; treating quality as measurable, not anecdotal * Advanced written and spoken English; can hold an architecture conversation with a CIO and a CISO in the same meeting, * 7+ years hands-on AI/ML engineering, of which 2+ years building LLM / agentic systems in production * 3+ years as technical lead or architect on client-facing delivery * Demonstrated ontology / knowledge-graph or semantic-layer work over messy real-world enterprise data * Experience with regulated or security-sensitive clients (BFSI, government, healthcare) and private deployment * Experience in consulting or a services business - comfortable being the technical face to a C-level client * Comfortable as the most senior technical person on a 2.5-FTE pod, with founders as sparring partners rather than a safety net ## Description * Run the Sprint 1 decision spike and write the decision record: one central private-cloud store vs. a semantic layer over the existing systems of record vs. ready platforms (Gemini Enterprise, Glean-class, Cohere-class, open components) - scored on security, access control, speed, cost and reversibility. * Design the ontology / semantic layer for the group: entities, relationships and business definitions spanning people, meetings, decisions, commitments, goals, deals, portfolio companies and documents. * Architect the connector layer as an execution layer, not just an ingestion layer - MCP / tool-calling (Composio-class or built) so agents can act in HubSpot, mail, Slack and internal systems, not merely read a stream of data. * Design role-scoped retrieval: the principle is that AI sees everything and people keep role-based access. Make that enforceable at the retrieval layer, not just in the UI, and evidence it to the client's security function. * Architect the agent layer: per-executive skills (Chief of Staff / CIO / CFO / COO), the OKR & drift coach delivered in Slack, and the process miner optimizer chain. * Choose and stand up the private deployment - VPC / on-prem / managed, model selection and routing, cost and latency envelopes. * Build the eval and observability harness: correctness, groundedness, access-boundary tests, regression suites before anything reaches an executive. * Establish standards and failure-mode design - human-in-the-loop boundaries for agents that take real actions, audit trails, rollback. * Stay hands-on: implement the critical pieces yourself, review the pod's work, and keep the build portable enough to redeploy as a NeuronsLab offering. * Explain all of the above to a C-level audience in plain language, in review sessions and working groups., * The current enterprise context-layer landscape - Glean-class platforms, Cohere-class "AI OS" products, Microsoft Copilot / Agents, Gemini Enterprise, Palantir-style foundries - and where each genuinely differs * GDPR and data-residency constraints for multi-jurisdiction European groups; what makes a private deployment defensible * Financial services / private-equity context - investment policy, portfolio reporting, board process - a strong plus * OKR / goal-management mechanics, enough to architect for them ## Related Videos - [When Should You Use an Agent? Architectural Trade-offs in Agentic Systems](https://www.wearedevelopers.com/videos/100109-when-should-you-use-an-agent-architectural-trade-offs-in-agentic-systems) - [How to govern Vibe Coding for the Enterprise](https://www.wearedevelopers.com/videos/100290-how-to-govern-vibe-coding-for-the-enterprise) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [The Missing Layer Between Enterprise Data and AI Agents](https://www.wearedevelopers.com/videos/100286-the-missing-layer-between-enterprise-data-and-ai-agents) - [Quality Strategy with a side of Swiss Cheese](https://www.wearedevelopers.com/videos/467-quality-strategy-with-a-side-of-swiss-cheese) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)