Forward Deployed Engineer

Carpiness s.r.o.; Barcelona; Presencial; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

Carpiness s.r.o. in Barcelona seeks a Forward Deployed Engineer (FDE) to deliver AI/Finance solutions end-to-end in a regulated enterprise.

This is a hands-on role that emphasizes shipping working software over lengthy specs. You’ll work directly with Finance stakeholders across FP&A, controllership, treasury and CFO functions to define problems, prototype quickly using Snowflake, Databricks, and LLMs, deploy responsibly, and measure business impact.

Formación

• 5+ years of software / engineering experience.
• Strong Python skills and experience building end-to-end applications.
• Production experience with LLM / AI applications.
• Hands-on experience with Snowflake Cortex and/or Databricks Genie.
• Experience building RAG solutions and working with vector search, embeddings and retrieval evaluation.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex or equivalent.
• Strong understanding of prompt engineering and LLM evaluation.
• Working knowledge of Snowflake and/or Databricks, plus cloud experience - Azure preferred.
• Solid SQL and data modelling skills.
• Experience with APIs, Git, CI/CD and modern development workflows.
• The ability to work directly with business stakeholders and translate business problems into technical solutions.

Responsabilidades

• Own the end-to-end delivery of AI solutions - from problem definition through deployment, adoption and measurable business outcomes.
• Work directly with Finance stakeholders across FP&A, controllership, treasury, procurement and CFO functions.
• Rapidly prototype and build vertical AI applications using Snowflake, Databricks, RAG pipelines and agentic workflows.
• Build full-stack solutions using Python, FastAPI/Flask, Streamlit, Databricks Apps or lightweight React.
• Get a first working prototype in front of users quickly, learn from real feedback and iterate.
• Deploy solutions within a governed and regulated enterprise environment with RBAC, data residency, audit and compliance.
• Build RAG pipelines, integrate LLMs and APIs, and connect AI solutions to enterprise systems and data.
• Instrument your solutions with usage, adoption and business outcome metrics.
• Handle the last mile - edge cases, business rules, data quirks, user training and adoption.
• Turn successful solutions into reusable patterns, components and assets for future AI applications.

Conocimientos

Python

LLM / AI applications

SQL

APIs

Git

CI/CD

Data modelling

Cloud platforms (Azure)

End-to-end delivery

Prompt engineering

Herramientas

Snowflake Cortex

Databricks Genie

LangChain

LangGraph

LlamaIndex

Databricks

Descripción del empleo

Forward Deployed Engineer (FDE) – AI / Finance | Barcelona

Occasional onsite in Barcelona

5+ years of experience

We're looking for an Forward Deployed Engineer (FDE) – AI / Finance to join a high-impact project focused on bringing AI and agentic solutions into Finance.

This is not a research role. And it's not a role where you spend months writing specifications before building anything.

You'll work directly with Finance stakeholders to understand real business problems, turn ambiguous ideas into working AI applications, deploy them into a regulated enterprise environment, and iterate with users until the solution delivers measurable value.

In short: you'll own the journey from "we have a problem" to "AI is solving it."

What you'll do

• Own the end-to-end delivery of AI solutions - from problem definition through deployment, adoption and measurable business outcomes.
• Work directly with Finance stakeholders across FP&A, controllership, treasury, procurement and CFO functions.
• Rapidly prototype and build vertical AI applications using technologies such as Snowflake, Databricks, RAG pipelines and agentic workflows.
• Build full-stack solutions using Python, FastAPI/Flask, Streamlit, Databricks Apps or lightweight React.
• Get a first working prototype in front of users quickly, learn from real feedback and iterate.
• Deploy solutions within a governed and regulated enterprise environment, taking care of RBAC, data residency, audit and compliance requirements.
• Build RAG pipelines, integrate LLMs and APIs, and connect AI solutions to enterprise systems and data.
• Instrument your solutions with usage, adoption and business outcome metrics.
• Handle the "last mile" - edge cases, business rules, data quirks, user training and adoption.
• Turn successful solutions into reusable patterns, components and assets for future AI applications.

What we're looking for

• 5+ years of software / engineering experience
• Strong Python skills and experience building end-to-end applications
• Production experience with LLM / AI applications
• Hands-on experience with Snowflake Cortex and/or Databricks Genie
• Experience building RAG solutions and working with vector search, embeddings and retrieval evaluation
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex or equivalent
• Strong understanding of prompt engineering and LLM evaluation
• Working knowledge of Snowflake and/or Databricks, plus cloud experience - Azure preferred
• Solid SQL and data modelling skills
• Experience with APIs, Git, CI/CD and modern development workflows
• The ability to work directly with business stakeholders and translate business problems into technical solutions

Nice to have

• Experience in Finance, Pharma, Life Sciences or CPG, familiarity with enterprise Finance platforms such as SAP, Workday or Oracle, and experience working in regulated environments.
• Experience in Forward Deployment, Solutions Engineering, Field Engineering or similar roles is also highly relevant.

What this role is not

This is not an ML research role, a pure backend role or an architecture-only position.

The models already exist.

Your job is to turn them into useful products, get them into the hands of users and make them deliver value.

Interested?

If you're an engineer who likes building things that people actually use - and you want to spend the next three years working on real-world AI transformation in Finance - we'd love to hear from you.