Agiloft - Staff Platform Engineer AI
Requirements
• Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience) • Minimum of 8 years of professional experience as a software engineer • Minimum of 3 years in a tech lead, architecture lead, or management role • Comfortable working with Python in core application code • Experience building modern, cloud-native applications using serverless technology (API Gateway, Lambda, DynamoDB, or similar) • Interest in building enterprise software with deep customer empathy, taking pride in contributing to a world class end-to-end user experience • Strong problem-solving, collaboration, teamwork and communication skills • Eagerness to learn and adapt to new technologies and tools • Proficiency in using relevant AI Tools in the SLDC (Cursor, GitHub Copilot) coding, and/or API integrations • Deep understanding of: • Version control systems (Git) • Relational databases and data modeling (Postgres preferred) • Infrastructure as Code in AWS (CloudFormation, SAM) • RESTful API design and documentation • CI/CD tools such as GitHub Actions or similar • Containerization and orchestration (Docker, ECS) • Enterprise-scale cloud engineering in AWS • Modern software development lifecycle on an agile product team • Interest in team leadership and career growth • Experience building applications on top of LLMs using commercial APIs • Familiarity with Postgres, query optimization, and database indexing • Exposure to data science tooling in Python (numpy, scipy, scikit-learn, pandas) • Experience with monitoring and observability across deployments and tenants • Interest in application security and cloud security • Background checks will be conducted on an ongoing basis every 3 years or as needed for individuals in this role.
Responsibilities
• Build and maintain software applications in our suite of enterprise software products • Work with product managers and designers to brainstorm bottom-up solutions to novel problems • Collaborate with AI engineers to efficiently utilize commercial large language model (LLM) APIs • Continuously improve the code quality, extensibility, scalability, and test coverage of software projects • Make architecture and cloud-engineering decisions in conjunction with other engineers • Develop and improve infrastructure-as-code stacks, CI/CD pipelines, and monitoring/observability tools • Improve internal developer tools, workflows, and best practices to enhance team efficiency • Provide consistent feedback to management regarding the quality of the team, the state of the tech stack, and relationships with stakeholders • Troubleshoot and resolve complex issues across the entire application stack • Mentor junior team members • Participate in incident response and disaster recovery efforts • Leverage AI-assisted tools to enhance productivity, streamline workflows, and support day-to-day activities
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