Location:

Barcelona (Hybrid / Versátil)Contract Type:

Contractor Full-Time / Enterprise Project EngagementAbout Xenon7

Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth.Job Summary

We are seeking a high-caliber

Forward Deployment Engineer (FDE)

to sit at the intersection of enterprise AI platforms and executive Finance business functions for our Fortune 100 enterprise client. This role bridges advanced AI platform engineering with direct business impact—translating ambiguous financial challenges into working AI applications, deploying them into regulated client environments, and iterating in tight loops to drive measurable ROI.Rather than building static models or waiting for formal spec sheets, you will operate as a product-minded technical lead. You will prototype user-facing tools in days, deploy agentic and RAG workflows on top of enterprise data stacks (Snowflake Cortex, Databricks Genie), and ensure high adoption across FP&A;, Controllership, Treasury, and CFO leadership.Key Responsibilities

End-to-End AI Application Prototyping & Delivery

Own the full lifecycle of AI solutions for Finance business units—from initial discovery with CFO stakeholders to production deployment, user adoption, and ROI measurementRapidly prototype vertical applications using Streamlit, Databricks Apps, FastAPI/Flask, or lightweight React interfaces within 1-2 weeks to gather real user feedbackHandle "last mile" execution: edge cases, data quirks, business rule exceptions, and user training to turn prototypes into sticky enterprise productsAgentic Systems & LLM Engineering





Build production-grade vertical AI tools leveraging Snowflake Cortex (Analyst/Search/Agents) or Databricks Genie (Genie Spaces, semantic models)Construct robust RAG pipelines incorporating advanced chunking, vector databases (Pinecone, Chroma, FAISS, Azure AI Search, Cortex Search), retrieval evaluation, grounding, and citationImplement LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex) and apply rigorous prompt engineering with hallucination and accuracy evaluation disciplineEnterprise Data & Regulated Integration

Deploy applications inside heavily regulated enterprise environments, adhering strictly to RBAC, data residency, audit, and compliance constraints (SOX, GxP)Connect solutions to governed datasets, semantic models, and core enterprise platforms (SAP, Workday, Coupa, ERP) via secure REST APIsInstrument all deployed apps with usage metrics, telemetry, and business outcome tracking from day oneStrategic Stakeholder Advisory & Pattern Extraction

Work directly with senior Finance leadership (CFO office, FP&A;, Controllership) to translate ambiguous operational friction into crisp technical roadmapsExtract reusable code components, prompt templates, evaluation harnesses, and retrieval patterns into shared enterprise assets for broader deploymentRequirements

Experience & Mindset

Experience: 5+ years of hands-on software development and full-stack AI application deploymentProduct-Shaped Builder: Strong bias for action; comfortable shipping rough prototypes in Week 1 over polished spec documents in Week 4Ambiguity Tolerance:



Proven ability to navigate vague business problems without predefined specificationsStakeholder Communication: Outstanding ability to interface directly with senior business leaders without requiring intermediary Business AnalystsMust-Have Technical Stack

Languages & Frameworks: Python, FastAPI/Flask, SQL, and UI frameworks (Streamlit, Databricks Apps, React)AI Platforms: Direct hands-on experience with Snowflake Cortex OR Databricks GenieLLM Engineering: Production experience with LangChain, LangGraph, LlamaIndex, vector search engines, and prompt evaluation harnessesCloud & DevOps: Deep working knowledge of Cloud platforms (Azure preferred, AWS/GCP acceptable), modern Git workflows, CI/CD, and basic MLOps awareness (observability, versioning via LangSmith, Datadog, etc.)Domain Competency (Finance Focus)

Solid foundational understanding of core Finance business processes (FP&A;, order-to-cash, procure-to-pay, record-to-report, close cycles) and common financial metrics (OPEX, EBITDA, gross margin, working capital)Nice-to-Haves & Certifications

Prior FDE, Solutions Engineer, or Field Engineer experience at high-growth AI/Data companies (Palantir, Snowflake, Databricks, OpenAI, Anthropic)Industry background in Life Sciences, Pharma, Healthcare, or CPG enterprise FinanceExperience with enterprise Finance software (SAP S/4HANA, Veeva, Workday Adaptive, Oracle Financials)Certifications: Snowflake Cortex, Databricks Certified, or Azure AI Engineer Associate (AI-102)What This Role Is NOT

Not a pure Data Scientist or ML Researcher: You will not be training or fine-tuning foundation models from scratch; you are applying existing models to business problemsNot a non-coding Architect: This is a 100% hands-on builder roleNot a pure Backend or MLOps Engineer: You must be comfortable owning the user-facing interface and direct business interaction

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📌 Forward Deployment Engineer (Madrid)
🏢 Xenon Seven
📍 Madrid