Forward Deployment Engineer

Xenon Seven; Gerona; Hybrid; EUR 120,000 - 180,000; Full time

Job summary

Xenon7 is seeking a Forward Deployment Engineer to join an enterprise AI initiative that spans Data, AI, and Finance functions. You will bridge advanced AI platform engineering with regulated, real-world financial environments, delivering production-ready tools that drive measurable ROI.

You will prototype rapidly, deploy agentic and RAG workflows on enterprise data stacks, and ensure high adoption across FP&A, Controllership, Treasury, and CFO leadership.

Qualifications

• 5+ years of hands-on software development and full-stack AI application deployment.
• Product-Shaped Builder with bias for action and rapid prototyping.
• Ability to navigate vague business problems without predefined specifications.
• Outstanding ability to interface with senior leaders directly without intermediaries.

Responsibilities

• Own full lifecycle of AI solutions for Finance units—from discovery with CFO to production deployment, user adoption, and ROI measurement.
• Prototype vertical applications in 1–2 weeks to gather real user feedback.
• Handle edge cases, data quirks, business rule exceptions, and user training to turn prototypes into enterprise products.
• Build production-grade vertical AI tools leveraging Databricks Genie.
• Construct robust RAG pipelines with vector databases and retrieval evaluation.
• Implement LLM orchestration frameworks and apply prompt engineering with evaluation discipline.
• Deploy applications inside heavily regulated enterprise environments with RBAC and data residency constraints.
• Connect solutions to governed datasets and core enterprise platforms via secure REST APIs.
• Instrument deployed apps with usage metrics and business outcomes from day one.
• Work with senior Finance leadership to translate operational friction into technical roadmaps.
• Extract reusable code components and patterns into shared enterprise assets.

Skills

Software development

AI deployment

Ambiguity tolerance

Stakeholder communication

Rapid prototyping

Product-minded leadership

Tools

Databricks Genie

Streamlit

FastAPI

Flask

SQL

React

LangChain

LangGraph

LlamaIndex

Pinecone

Chroma

FAISS

Azure

AWS

GCP

Datadog

LangSmith

Databricks Apps

Job description

Location: Barcelona (Hybrid / Flexible)

Contract Type: Contractor Full-Time / Enterprise Project Engagement

About 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 (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 measurement
• Rapidly prototype vertical applications using Streamlit, Databricks Apps, FastAPI/Flask, or lightweight React interfaces within 1-2 weeks to gather real user feedback
• Handle "last mile" execution: edge cases, data quirks, business rule exceptions, and user training to turn prototypes into sticky enterprise products

Agentic Systems & LLM Engineering

• Build production-grade vertical AI tools leveraging 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 citation
• Implement LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex) and apply rigorous prompt engineering with hallucination and accuracy evaluation discipline

Enterprise 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 APIs
• Instrument all deployed apps with usage metrics, telemetry, and business outcome tracking from day one

Strategic Stakeholder Advisory & Pattern Extraction

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

Requirements

Experience & Mindset

• Experience: 5+ years of hands-on software development and full-stack AI application deployment
• Product-Shaped Builder: Strong bias for action; comfortable shipping rough prototypes in Week 1 over polished spec documents in Week 4
• Ambiguity Tolerance: Proven ability to navigate vague business problems without predefined specifications
• Stakeholder Communication: Outstanding ability to interface directly with senior business leaders without requiring intermediary Business Analysts

Must-Have Technical Stack

• Languages & Frameworks: Python, FastAPI/Flask, SQL, and UI frameworks (Streamlit, Databricks Apps, React)
• AI Platforms: Direct hands-on experience with Databricks Genie
• LLM Engineering: Production experience with LangChain, LangGraph, LlamaIndex, vector search engines, and prompt evaluation harnesses
• Cloud & 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, Databricks, OpenAI, Anthropic)
• Industry background in Life Sciences, Pharma, Healthcare, or CPG enterprise Finance
• Experience with enterprise Finance software (SAP S/4HANA, Veeva, Workday Adaptive, Oracle Financials)
• Certifications: 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 problems
• Not a non-coding Architect: This is a 100% hands-on builder role
• Not a pure Backend or MLOps Engineer: You must be comfortable owning the user-facing interface and direct business interaction