MLOps Engineer – GenAI Platform, AWS

This is a fully remote position, open to applicants in Poland.

📋 Description

• Construct and uphold a secure, scalable AWS infrastructure that supports a production-focused agentic AI platform.

• Provision and oversee cloud infrastructure utilizing infrastructure-as-code methodologies, ideally with Terraform.

• Containerize and deploy components of the AI platform along with supporting services in AWS, incorporating ECS.

• Set up IAM, manage secrets, and implement encryption alongside other security measures for a regulated environment.

• Execute monitoring, logging, security scanning, and performance controls throughout the platform.

• Create Python services and REST APIs that provide data and business functionalities for AI-driven workflows.

• Contribute to solutions involving retrieval-augmented generation.

• Assist in orchestrating LLM and integrating AI agents with external services and business operations.

• Assess and enhance retrieval quality, response precision, and overall system dependability.

• Design and maintain automated unit and integration tests using pytest.

• Engage in technical design conversations, review pull requests, and adhere to GitHub-based team processes.

• Take full ownership of components that are production-ready, secure, and maintainable.

⛳️ Requirements

• Practical experience in building and managing production AI/ML or GenAI platforms within AWS.

• Strong working knowledge of AWS infrastructure, preferably including ECS, IAM, and Secrets Manager.

• Experience in provisioning and managing cloud infrastructure as code, ideally using Terraform.

• Expertise in containerization with Docker and a solid understanding of production container deployment practices.

• Familiarity with establishing cloud security, access controls, secrets management, and encryption.

• Understanding of monitoring, logging, and operational controls for production systems.

• Capability to build and expose data and application features through REST APIs.

• Practical experience in Python and the ability to independently create production-quality services and automation.

• Experience in writing automated unit and integration tests using pytest, fixtures, and mocking.

• Background in implementing security scanning and enhancing platform performance and reliability.

• Familiarity with GitHub-based development workflows, including feature branches, pull requests, and code reviews.

• Excellent communication skills, ownership of delivered solutions, and proactive identification of technical risks and enhancements.

• Nice-to-have: experience with production LLM systems, AI agents, agentic workflows, retrieval-augmented generation, LLM orchestration, tool calling, response evaluation, guardrails, regulated environments, telecommunications products, or customer-service processes.

🏝️ Benefits

• Equal opportunities in recruitment, career advancement, and leadership roles.

• A diverse and inclusive workplace culture.

• Fully remote work options available.