🤖 Can you imagine contributing to a large-scale AI ecosystem that will support more than 100 AI initiatives across multiple business domains?

Join our expert team to work on a cutting-edge AI platform, contributing to the development of conversational agents, RAG solutions, enterprise integrations and multi-agent architectures. You will apply your knowledge of Python, AWS Bedrock, Agent frameworks and serverless technologies to build scalable, secure and reusable AI solutions.

At ERNI, you are never just a number. Even if you work on an external project, you will feel part of the team and always supported.

How do we make this happen? 🤔

With people. Besides your team and manager, you will have several support figures like a godparent, who will help you with the practical and administrative aspects of daily life during your first 6 months.

And the second most important person after you, your mentor, who will guide you through your entire onboarding and career at ERNI. You will have regular 1:1 meetings with them, and recurrently, you will work on your development plan to define your short-, medium-, and long-term goals.

We strongly encourage growth and continuous training. Each person has an individual development plan, mentoring, and access to internal technical communities. We aim for you to learn, experiment, and evolve within an environment where teamwork and support from more senior colleagues are key.

What you will bring 🤝

• Strong Python experience including type hints, pytest and clean code practices.
• Hands-on experience building LLM applications with AWS Bedrock, prompting, memory management and tool calling.
• Production experience with AWS serverless services such as Lambda, DynamoDB, API Gateway, Kinesis and IAM.
• Experience with Infrastructure as Code using AWS CDK or Terraform.
• Knowledge of agent frameworks such as Strands, LangGraph, LangChain or similar.

You will be responsible for designing, building and deploying AI agents and generative AI solutions. You will develop scalable serverless architectures, integrate AI capabilities with enterprise systems, and implement observability, security and governance controls to ensure reliable production environments. You will also collaborate with multidisciplinary teams to evolve PoCs into production-ready solutions while driving scalability, maintainability and operational excellence.

What if the project ends?😅

We work on a wide variety of projects, technologies, and sectors, allowing you to keep growing in different environments. If a project ends or you feel ready for a new challenge, we will find another one that aligns with your professional development.

Our working model 👩‍🔬

We ask you to be available for key meetings. Need to leave for a doctor’s appointment or to pick up your child from school? No problem. We trust you to deliver quality work within your 40-hour workweek.

Our model is hybrid: we usually go to the office 2 days a week, though this depends on the project and team, but we love seeing each other’s faces; the best stories always happen in the office!

AI Agent Productivization Engineer

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