Implementation Engineer, AI Agents

About Autoflows

Autoflows is an agentic after-sales platform for automotive retail.

AI Agent Engineer

Department: AI Delivery

Location: Copenhagen

Working model: Onsite

Reports to: AI Product Lead

Salary: Competitive

The Role

As an AI Agent Engineer, you will build, deploy, debug and continuously improve the conversational agents running across our clients.

We deploy AI agents across dealerships in Europe that handle customer conversations end to end across voice and messaging. Our agents identify the right moment to contact customers about service, MOT, warranty and other after‑sales opportunities, then handle the conversation, book the appointment and write the outcome back into the dealership's systems.

Our platform connects with DMS, CRM and OEM data, turning after‑sales work that traditionally sits in queues into work that runs itself.

We are now scaling across clients, markets and languages. That requires us to build a delivery capability that does not depend on one person knowing how everything works.

You Will Work Across The Full Lifecycle

Build → Test → Deploy → Monitor → Debug → Improve

You will start closely with the AI Product Lead and progressively take independent ownership of production agents and client implementations.

The role is not just about configuring agents. With time you will also help build the tooling and systems that make agents easier to deploy, operate and maintain at scale. Architectural decisions for the core agentic platform stay with the AI Product Lead; your platform involvement is about the tooling layer around agents, not the underlying architecture itself.

What You'll Do

Agent development

Build and tune agents across voice, chat, SMS and WhatsApp

Develop prompts, tools, workflows, guardrails and fallback paths

Test agents against realistic customer scenarios

Improve agent behavior using production data and conversation analysis

Production & implementation

Diagnose and fix live issues such as model failures, mispronunciations, failed tool calls, broken workflows and missing fallback paths

Own new agent deployments as dealership clients onboard

Adapt agents to different processes, languages and markets

Work directly with clients when technical input is required

Identify root causes rather than applying temporary fixes

Integrations

Work with DMS, CRM and other dealership systems

Configure and troubleshoot integrations for customer data and workshop bookings

Build reusable patterns for recurring integration requirements

Agentic platform tooling

We are building an agentic platform, not a collection of manually maintained bots. You will be encouraged to identify repetitive work and turn it into systems. This may include:

Automated testing and evaluation

Monitoring and regression detection

Automated diagnosis of recurring failures

Self‑healing or automated recovery for well‑understood failure modes

Automated deployment and configuration

Reusable agent components and workflows

Agent‑assisted documentation and operational tooling

Systems that allow agents to improve from production feedback within defined quality and safety boundaries

Architecture & delivery

Work with the AI Product Lead on complex architectural decisions

Help determine when to use prompting, workflow logic, deterministic code, specialised agents or other approaches

Document recurring solutions and contribute to the team's technical playbook

Help establish standards that make future deployments faster and more reliable

What We're Looking For

This role sits between AI, technology and human behaviour. Technical ability is necessary, but technical ability alone is not enough. Our agents speak to real customers. You need to care about what the interaction feels like, not just whether the system technically works.

Technical

Hands‑on experience building with LLMs and AI APIs

Strong understanding of prompting and model behaviour

Experience debugging AI or software systems

Ability to reason through ambiguous technical problems

Comfort working without a finished specification

Ability to learn unfamiliar platforms and systems quickly

Human & social

Strong social skills and clear communication

Natural curiosity about how people think, speak and respond

Ability to look at an interaction from the customer's perspective

Good judgement about tone, context and conversational nuance

Comfortable speaking directly with clients and asking the questions needed to understand a problem

Able to explain technical issues clearly to non‑technical people

Open to feedback and willing to change your approach when evidence shows it is not working

Interested in how language and culture affect conversational AI

Builder mindset

You investigate why something failed rather than simply fixing the visible symptom

You notice repetitive work and look for ways to automate it

You are comfortable experimenting, testing and iterating

You think beyond the individual agent and look for ways to improve the underlying platform

Strong plus

Conversational AI or agent‑building experience

Voice AI, chatbots or workflow automation

API and systems integration experience

Experience with tools, function calling or agentic workflows

Experience operating production AI systems

Experience working across multiple languages

Experience with CRM, ERP, DMS or similar business systems

Automotive experience is not required.

Success in the Role

Independently diagnose and resolve most common agent failures

Build and deploy agents with limited supervision

Own production improvements from investigation through deployment

Handle recurring integration problems

Turn repeated manual work into reusable systems

Improve the reliability and scalability of our agent platform

Reduce the amount of hands‑on implementation required from the AI Product Lead

The Team

You Will Work In a Small AI Delivery Team

AI Product Lead – Owns product direction, architecture, priorities, technical standards and complex technical decisions

AI Agent Engineer – Owns agent development, implementation, production debugging and platform improvements

AI/ML Student – Supports testing, evaluation, research, data work, experimentation and implementation

Because the team is small, you will have significant ownership and direct exposure to the systems we are building.

#J-18808-Ljbffr