AI-Directed Software Engineer

Accountabilities • Deliver full-stack software solutions: Own features from initial requirements and technical specifications through development, testing, demonstrations, deployment, and production support.

• Direct AI-powered development: Use AI coding assistants to generate and refine code, APIs, user interfaces, SQL queries, infrastructure configurations, and workflows while breaking down requirements into clear, executable tasks.

• Ensure code quality and reliability: Review, validate, test, debug, and harden AI-generated output, addressing correctness, edge cases, security vulnerabilities, performance issues, and production readiness.

• Manage cloud infrastructure and deployments: Configure and deploy applications using AWS, Docker, Kubernetes, Helm, and infrastructure-as-code tools, ensuring reliable operations and scalable environments.

• Develop AI-powered capabilities: Design, implement, and deploy Amazon Bedrock-based agents, including tool integrations, action groups, retrieval-augmented generation (RAG), Knowledge Bases, and appropriate guardrails.

• Maintain secure and efficient cloud operations: Apply least-privilege access controls, monitor application performance through CloudWatch, troubleshoot failures, and manage infrastructure and AI-related costs.

• Improve engineering productivity: Track delivery speed and development cycle times, refine prompts and AI-assisted workflows, and establish repeatable practices for AI-directed software delivery.

• Collaborate across the development lifecycle: Translate product needs into technical solutions, document workflows, communicate decisions clearly, and contribute to the evolution of engineering standards and development processes.

Requirements

• Software engineering fundamentals: Strong understanding of APIs, distributed systems, debugging, data flows, and the interactions between application components at scale.

• AWS experience: At least three years of hands-on experience building and operating production workloads on AWS, with a solid understanding of IAM, VPC networking, cloud service reliability, and cost management.

• Infrastructure as code: Practical experience managing AWS infrastructure through CloudFormation, preferably, or alternatives such as AWS CDK or Terraform.

• Full-stack capabilities: Comfortable working across backend services, frontend applications, databases, and deployment configurations, adapting to different technologies as project needs evolve.

• Containers and orchestration: Familiarity with Docker and Kubernetes, including the ability to investigate failing pods, understand deployment manifests, and modify Helm configurations, or demonstrate the ability to develop these skills quickly.

• AI development tools: Demonstrated experience using AI coding assistants such as Claude Code, Cursor, GitHub Copilot, or comparable tools to deliver real software projects.

• Critical review and problem-solving: Ability to identify subtle issues in AI-generated code, challenge assumptions, troubleshoot complex problems, and make sound technical decisions.

• Adaptability and ownership: Comfortable working in a fast-moving, ambiguous environment, prioritizing working software and practical outcomes while maintaining high quality standards.

• Communication skills: Strong written communication skills, particularly when creating precise specifications, prompts, technical documentation, and instructions for AI systems.

• Preferred AI expertise: Hands-on experience with Amazon Bedrock, model integration, agent development, action groups, RAG, Knowledge Bases, and Guardrails. Experience evaluating large language model outputs in production through test harnesses, evaluation datasets, failure handling, and human-in-the-loop controls is highly desirable.

• Additional assets: Familiarity with Java, Jersey, Angular, React, TypeScript, PostgreSQL, Python, or multi-tenant SaaS architectures. Experience in library technology, public-sector solutions, or related domains is also beneficial.

Benefits

• Remote work: Fully remote employment, with the opportunity to work from the United States.

• Full-time position: A regular, full-time role offering the opportunity to contribute to meaningful software development initiatives.

• Professional growth: Exposure to AI-directed software engineering, cloud-native development, and emerging agentic AI technologies.

• Technical ownership: The opportunity to work across the full software stack, influence development practices, and deliver solutions from concept to production.

• Innovation-focused environment: An opportunity to help shape repeatable AI-driven engineering workflows and improve development speed and consistency.

• Collaborative culture: Work alongside a team focused on innovation, problem-solving, and building technology that improves operational efficiency.

• Compensation and additional benefits: Salary, healthcare coverage, paid leave, retirement benefits, and other employment perks were not specified in the available job description and should be confirmed during the recruitment process.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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