AI Agents
Specialist

From proof of concept to agents running in production

We are looking for a highly innovative and technically skilled AI Agents Specialist to join our Process Automation team. This role focuses on leveraging cutting-edge Generative AI and Large Language Models to design, build, and deploy sophisticated AI agents and agentic workflows that address complex business challenges in customer experience, marketing, sales, and internal operations.

The ideal candidate blends strong software engineering principles with deep knowledge of prompt engineering, LLM orchestration, and MLOps best practices. You will be responsible for transforming proof-of-concept AI ideas into production-ready, scalable agents that act autonomously, communicate effectively, and provide measurable value.

This role demands a market-first, data-driven approach, where you are comfortable experimenting, iterating fast, and building novel solutions with a global reach.

What you will actually do

• Architecting Agentic SystemsDesign and implement multi-step, multi-agent systems and agentic frameworks (LangChain, Dify, n8n, LlamaIndex, or custom solutions) that perform complex tasks, including tool use, memory management, planning, and self-correction.
• LLM OrchestrationSelect, fine-tune, and integrate various LLMs and foundation models (Gemini, OpenAI, Anthropic and others) to optimize agent performance, latency, and cost efficiency.
• Prompt Engineering MasteryDevelop and refine advanced prompt engineering strategies, including few-shot learning, Chain-of-Thought and Retrieval-Augmented Generation, to ensure agents deliver high-quality, relevant, and accurate outputs.
• Scalable DeploymentDeploy and manage production-grade AI agents, focusing on scalability, security, and low latency, primarily on cloud platforms (GCP preferred, or Azure and AWS).
• Tool IntegrationEquip agents with the tools, APIs, and access to internal systems and databases they need to execute real-world actions and retrieve real-time data, ideally including AI-powered app development platforms such as Lovable.
• MLOps for AgentsApply MLOps principles to monitor agent performance, manage version control for prompts and models, and establish continuous feedback loops for iterative refinement.
• Proof-of-Concept & ExperimentationLead research and development sprints to test emerging agent capabilities, micro-LLMs, and new model architectures to maintain a competitive edge.
• Cross-Functional CollaborationWork closely with engineering, product, and business teams to identify high-impact use cases and integrate AI agents into existing commercial products and workflows, including low-code automation platforms.
• Ethical AIEnsure all developed agents comply with ethical guidelines, data privacy laws, and industry standards, focusing on transparency and control.

Technical & platform skills

Experience

Minimum 1 year of experience in Machine Learning Engineering, Software Development, or AI and NLP specialization, with a dedicated focus on building and deploying LLM-based applications.

Python & engineering

Expertise in Python and strong software engineering fundamentals (OOP, testing, version control with Git, CI/CD).

Orchestration & RAG

Proven hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, Dify), RAG implementation, and prompt engineering.

LLM APIs

Familiarity with major LLM APIs and models (OpenAI/GPT, Gemini/Google AI Studio, Anthropic/Claude).

MLOps

Experience with MLOps tools and practices for monitoring, logging, and deploying models (MLflow, Kubeflow, Vertex AI, Azure Machine Learning).

Cloud & containers

Experience deploying solutions on cloud platforms (GCP, Azure, or AWS), focusing on serverless and containerized deployment (Docker, Kubernetes).

Data engineering

Solid understanding of data modeling, data transformation, and ETL processes to prepare data for RAG and agent context.

Behavioral skills

Innovator and Builder

A strong bias towards action and an innate drive to build novel, market-ready solutions rather than just research.

Systematic Problem Solver

Ability to handle the complexity and non-determinism of agentic systems, designing robust fallbacks and validation layers.

Business Translator

Excellent communication skills to bridge the gap between complex AI capabilities and tangible business outcomes.

Ambition and Agility

Thrives in a fast-paced R&D environment, capable of quick iteration, pivoting strategies, and managing the ambiguity of new technologies.

Detail-Oriented

Meticulous approach to prompt design, performance measurement, and ensuring model reliability.

Analytical Mindset

Capable of putting data first and obsessed with analytical initiatives and insight building, always with client satisfaction and business results in mind.

AI Readiness

Interest and nativeness in using AI as a partner to deliver efficient value, respecting security and privacy regulations.

Innovation Lover

Someone seeking permanent growth and desiring to be part of innovative solutions.

Results-Oriented Zeal

An unwavering commitment to the client’s bottom line, pushing boundaries to chase the best overall performance and business goals.

Not required. Noticed.

• Experience with Google Cloud Platform services (Vertex AI, Dataflow, BigQuery, Generative AI Studio, Gemini API).
• Deep knowledge of fine-tuning or training specialized LLMs or small language models.
• Contributions to open-source ML and AI projects, or relevant academic publications.
• Experience in AdTech, MarTech, or Customer Experience domains.
• Professional certifications in Machine Learning or Cloud AI platforms.
• Experience with final clients in an agency or consultancy role.