Principal Software GenAI Engineer

Role Summary

The Principal Software GenAI Engineer is a senior technical leader responsible for designing and building scalable platforms, tools, and workflows that enable teams to develop, deploy, and manage machine learning and generative AI solutions at scale; working heavily within cloud environments like Amazon Web Services, the role combines software engineering, MLOps, and DevOps expertise to drive the adoption of modern AI technologies, shape technical strategy, and foster a high-performing engineering culture across the organization.

Key Responsibilities • Lead the design and development of scalable platforms and tooling for Data Science, MLOps, and LLMOps workflows • Define and execute strategies for deploying, serving, and monitoring large language models using services like Amazon SageMaker and Amazon Bedrock • Implement Infrastructure-as-Code (IaC) using tools such as AWS CDK and CloudFormation to manage cloud environments • Design and maintain CI/CD pipelines using tools like GitHub Actions, AWS CodePipeline, and Jenkins • Build and integrate monitoring and observability solutions using tools such as CloudWatch, Prometheus, and Grafana • Ensure high software quality through test-driven development (TDD) and automated testing practices • Make and guide architectural decisions for scalable, reliable, and maintainable systems • Collaborate with architects, product leaders, and stakeholders to define long-term technical strategy • Apply and enforce security best practices using DevSecOps principles and cloud-native tools • Mentor engineers and promote knowledge sharing, best practices, and a strong engineering culture • Drive cross-team collaboration to enable ML/AI innovation across the organization.

Requirements • Extensive experience in DevOps/MLOps roles, building and scaling ML/AI platforms in cloud environments like Amazon Web Services • Strong hands-on experience with AWS services such as Amazon SageMaker, Amazon Bedrock, S3, EC2, Lambda, IAM, VPC, and container services • Advanced expertise in Infrastructure-as-Code using AWS CDK, CloudFormation, or Terraform • Proven experience designing end-to-end MLOps pipelines using tools like MLflow or SageMaker Pipelines • Strong experience with containerization and orchestration using Docker and Kubernetes • Deep knowledge of CI/CD practices and tools such as GitHub Actions, Jenkins, and GitOps workflows • Solid understanding of advanced DevOps concepts like blue/green deployments, canary releases, and system resilience • Strong knowledge of cloud security, governance, and compliance frameworks • Demonstrated ability to lead technical initiatives and influence cross-functional teams • Deep understanding of the machine learning lifecycle, including deploying and managing LLMs and generative AI systems in production environments

P.S: The location for this role is Latvia. The hiring company is open to relocating the potential candidate to this country.

Note: Only qualified candidates will be contacted.

Job Type: Full-time

Pay: ₦3,500,000.00 - ₦5,000,000.00 per month

Application Question(s): • This role is resident in Latvia. Do you have a Schengen Travel Visa? If no, are you willing to relocate to Latvia?

The company is willing to help get the visa done if there's a match and you are really interested in the role.

Experience: • building and scaling ML/AI platforms in cloud environments: 7 years (Required)

Work Location: Remote