Activesoft, Inc.

Compensation

Full Description

The Opportunity As AI/ML adoption accelerates, the need for robust data management has never been more critical. We re building a new-to-market platform that orchestrates the full data lifecycle from ingestion and enrichment to discovery and dissemination. Join us as a Software Engineer to help create the metadata hub that will enable AI/ML at scale, streamlining how organizations discover, access, use, and share data across their entire ecosystem. What You ll Do Work alongside experienced engineers leveraging a modern tech stack. You ll develop, test, and productize solution components that integrate relational databases, microservices, cloud services, and containerized applications. Responsibilities • Build the data infrastructure that powers next-generation AI/ML at scale. You ll design and optimize high-performance pipelines that ingest, transform, and deliver data across enterprise ecosystems, working with relational databases including Oracle, PostgreSQL, and MySQL. • Develop cloud-native services using NestJS and Python while leveraging AWS infrastructure (Glue, S3, Lambda, ECS/EKS). Deploy production systems using Docker, Kubernetes, and Terraform, ensuring performance, reliability, and scalability at every layer. • Ship quality code through comprehensive testing and CI/CD workflows. Architect data pipelines that fuel LLM training and AI workloads, enabling seamless integration across diverse datasets. • Stay current with emerging technologies, including modern data lake / lakehouse frameworks, and help define the future of enterprise data management. Technical Foundation • 4+ years of progressive software development experience. • Proficiency with relational databases (Oracle, PostgreSQL, MySQL, etc.). • Experience with modern data lake/lakehouse technologies (Apache Iceberg, Spark, etc.). • Exposure to AWS services (Glue, S3, Lambda, EKS/ECS). • Background with Terraform for infrastructure as code. • Familiarity with workflow orchestration tools (Airflow, Step Functions, Argo, etc.). • Working knowledge of Docker and Kubernetes for containerization. • Proficiency with GitLab or similar tools for CI/CD and version control. • Experience in designing, building, and scaling AI/ML data processing systems including integrating and operationalizing LLMs in production environments.