AI Enablement Engineer

United States Digital Space LLC; Berlin; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

United States Digital Space LLC is seeking an AI Enablement Engineer to enhance internal workflows using AI. This role involves close collaboration with various teams to identify and build tools that optimize operations. Candidates should have over 3 years of software engineering experience and excellent skills in Python and AI integration.

The position requires a hybrid work model, with at least 3 days a week in one of the Berlin, Iasi, or London offices. Join us in transforming how teams work with AI!

Qualifikationen

• 3+ years of professional software engineering experience in production systems.
• Experience with modern LLM tooling: agent frameworks, prompt engineering.
• Fluent English is required.

Aufgaben

• Identify high-leverage workflows that can adopt AI.
• Build internal tools to integrate with existing SaaS stack.
• Drive adoption and measure success through real usage.

Kenntnisse

Python

AI architecture

SaaS API integration

Stakeholder communication

LLM tooling

Technical enablement

Tools

AWS

Snowflake

Terraform

HubSpot

Notion

Linear

Gong

Jobbeschreibung

About the Role

the company helps financial institutions make smarter, safer decisions with the power of AI. Internally, we believe the companies that win the next decade will be the ones that turn AI from a tool into a multiplier - embedded into how every team works, not just shipped as a product feature.

We're looking for an AI Enablement Engineer to make this the reality at the company. This is a high-leverage, internal-facing engineering role: you won't be building features for our customers, you'll be building the tools, integrations, and workflows that make every Taktilian faster and better at their job - from engineers shipping code, to GTM teams responding to customers, to operations closing the books.

You’ll be the first hire dedicated to this mission, working closely with team leads across the company to identify, build, and scale the AI workflows with the biggest impact. the company is a hybrid company. This role requires working at least 3 days per week from one of our offices in Berlin, Iasi, or London.

What you’ll do

• Find the highest-leverage workflows. Embed with teams across Engineering, GTM, Customer Success, Finance, and Operations to identify where AI can remove the most friction.
• Build internal tools and agents end-to-end that wire the company's SaaS stack (HubSpot, Notion, Linear, Gong) into our engineers' and operators' daily workflows. Own scope, design, implementation, rollout, and iteration.
• Evolve AI architecture based on internal customer needs and tangible, measurable improvements.
• Drive adoption, not just deployment. Run hands‑on workshops, pair sessions, and office hours to teach teams how to actually use what you ship. Measure success in real adoption and time saved, not features delivered.
• Partner with Security and IT on governance. Apply least‑privilege principles from day one. Build the guardrails, access scoping, and audit trails that let us move fast on AI without exposing customer data or production systems.
• Stay on the frontier. Know when new tools and models release, which ones are worth experimenting with, and bring the best of it back into the business.

Requirements

• 3+ years of professional software engineering experience, with a track record of shipping production systems end-to-end.
• Production‑grade coding ability in Python in cloud‑native environment.
• Hands‑on experience building with modern LLM tooling – agent frameworks, tool use, prompt engineering, MCP, evals. You've shipped something real, not just experimented in a notebook.
• Strong SaaS API integration experience – REST, webhooks, OAuth, idempotency, the messy realities of stitching real systems together.
• Exceptional communication and stakeholder skills with technical and non‑technical operators alike.
• A bias for adoption over abstraction. You measure your work by who's using it next week, not by how elegant the architecture is.
• Fluent English, both written and spoken.

Ideal, but not required

• Prior experience in a technical enablement, internal tools, DX, or platform engineering role.
• Experience integrating unstructured data into AI workflows.
• Familiarity with AI governance and data classification in a regulated industry.
• You've run workshops or internal trainings and enjoy doing them.

Our Stack

• AI: Claude
• Programming Language: Python
• Data Platform: AWS, Snowflake, dbt, Terraform
• Internal Tools: Notion, Linear, HubSpot, Gong, Ramp