AI Enablement Engineer

About the role

Taktile builds AI-powered decisioning software for financial institutions so they can make better and safer choices. The company believes the organizations that thrive over the next decade will be the ones that use AI as a force multiplier across the whole business, rather than limiting it to customer-facing features.

This position is an internal, high-impact engineering role focused on creating the systems, integrations, and workflows that help every team member work faster and more effectively. You will not be working on customer product features; instead, you will build the infrastructure that supports engineers, go-to-market teams, customer success, finance, and operations.

You will be the first person hired specifically for this mission and will work closely with team leads to find, build, and scale the AI use cases with the greatest business value. The role is part of a hybrid setup and requires working from one of the company offices in Berlin, Iasi, or London for at least 3 days each week.

Key responsibilities

• Work directly with teams across engineering, GTM, customer success, finance, and operations to uncover the workflows where AI can eliminate the most effort and friction.
• Design and deliver internal tools and agents from start to finish, connecting the company’s SaaS systems such as HubSpot, Notion, Linear, and Gong into daily work processes for engineers and operators.
• Continuously adapt AI architecture based on internal user needs and measurable gains in productivity and efficiency.
• Encourage real usage, not just rollout, by leading workshops, pair sessions, and office hours that help teams adopt what you build.
• Collaborate with Security and IT to apply strong governance practices, including least-privilege access, guardrails, scoped permissions, and auditability to protect customer data and production systems.
• Keep up with the latest AI tools and models, assess which ones are worth testing, and feed useful discoveries back into the business.

Requirements

• At least 3 years of professional software engineering experience, including ownership of production systems end to end.
• Strong Python development skills in a cloud-native environment.
• Practical experience with modern LLM tools such as agent frameworks, tool use, prompt design, MCP, and evaluation methods, with shipped production work rather than only prototype experiments.
• Solid SaaS integration experience covering REST APIs, webhooks, OAuth, idempotency, and the real-world challenges of connecting multiple systems.
• Excellent communication and stakeholder management skills with both technical and non-technical collaborators.
• A strong preference for solutions that drive adoption and usage over purely theoretical or abstract architecture.
• Fluency in English, both spoken and written.
• Nice-to-have experience in technical enablement, internal tools, developer experience, or platform engineering.
• Exposure to unstructured data in AI workflows is beneficial.
• Familiarity with AI governance and data classification in regulated industries is a plus.
• Experience running workshops or internal trainings is advantageous and welcome.

Technology stack

• AI tooling: Claude
• Programming language: Python
• Data and infrastructure: AWS, Snowflake, dbt, Terraform
• Internal business tools: Notion, Linear, HubSpot, Gong, Ramp

Work arrangement

This is a hybrid role based in Berlin, Germany, with collaboration also tied to offices in Iasi and London. On-site attendance is required for at least 3 days per week.