Software Engineering – Intelligent Platforms (Mid)

Role overview

Develop backend services, agents, and automation workflows for platforms that interact with technical and business systems. You’ll work hands-on with AI-enabled capabilities and express infrastructure, deployments, agent behavior, and operational processes as version-controlled artifacts that can be reviewed and tested. The role is collaborative, involving software, systems engineering, and security colleagues in a secure delivery environment.

Responsibilities

- Build and maintain backend services, microservices, APIs, and orchestration logic for intelligent platforms. - Develop agents and LLM-enabled workflows for analysis, decision support, automation, and system interaction. - Use infrastructure-as-code practices to provision and manage cloud environments. - Work with systems engineers and security specialists to translate requirements and controls into implementation. - Contribute to Git-based reviews, documentation, CI/CD pipelines, and secure deployments aligned with authorization requirements. - Document code, agent behavior, and system interactions; help make infrastructure, workflows, and operational artifacts testable and maintainable.

Requirements

- Bachelor’s degree and at least four years of professional software development experience. - Proficiency in a modern programming language; Python is preferred, with Java or Go also suitable. - Experience building backend services, APIs, or microservices. - Exposure to AI/ML, large language models, or intelligent automation through professional work or applied projects. - Familiarity with infrastructure-as-code concepts and collaborative GitLab or GitHub development practices. - Ability to work with evolving or ambiguous requirements and to hold and maintain an active Secret security clearance.

Nice to have

- Experience building agents, orchestrating workflows, or using LLM tools, functions, or retrieval patterns. - Familiarity with Docker, Kubernetes, cloud platforms such as AWS GovCloud, or secure AI systems. - Security+ or equivalent IAT Level II certification. - Experience expressing configuration, policies, workflows, or documentation as version-controlled code.