Software Engineer with Expertise in Agentic AI, Generative AI, API & Web Development (Only G.C / U.S.C)
6+Months
St. Louis, MO (Onsite 4x a week)
Position Summary:
We are on the hunt for a dedicated and talented Software Engineer who possesses a rich experience in API creation and integrating web application systems, coupled with proficiency in constructing secure and scalable backend solutions. With no less than 6 years in the field, the candidate should have an extensive understanding of Python programming, particularly with the FastAPI framework, and demonstrate expertise in continuous integration and deployment utilizing tools such as Azure DevOps (ADO) and GitHub. This role is pivotal for architecting, crafting, and implementing resilient web services and APIs, working in tandem with diverse teams to ensure secureness, efficiency, and code maintainability.
Essential Competencies in Generative and Agentic AI concepts include understanding and applying:
Generative AI (GenAI) — Essential Understanding:
• Foundation Models: Utilize immense, broadly capable pre-training models adaptable to various tasks.
• Instruction Dynamics: Recognize the influence of user and system-driven input, its restrictions, and the desired tone.
• Contextual Limitations: Work within the operative short-term memory constraints for processing text or imagery content.
• Retrieval-Augmented Strategies: Leverage databases and search engines to enhance model outputs with necessary context.
• Content Embeddings: Employ vector representations for semantic content search and comparison.
• Model Customization: Choose between detailed model tuning or modular adapters for task-specific model behavior.
• Function Integration: Empower the model to utilize computational resources, interface with databases, and perform systematic operations.
• Output Structuring: Generate outputs adhering to specified JSON schema or constraints to ensure reliable integration.
• Model Assessment: Evaluate model output through various metrics and ensure quality control.
• Output Verification: Address confidently incorrect model outputs through various strategies encompassing knowledge databases and design patterns.
• Safety Protocols: Enforce policies to guide usage, ensure safe data practices, and maintain compliance records.
Agentic AI — Essential Understanding:
• Interactive Models: Develop systems capable of goal-oriented planning and iterative actions.
• Autonomy Scale: Create solutions spanning from suggest-only to fully automated systems, with caution in enterprise contexts.
• Strategic Decomposition: Break down objectives into manageable tasks and sequence operations effectively.
• Operational Implementation: Facilitate interaction with toolsets and APIs to actualize state alterations.
• Long-term Memory: Manage persistent data pertinent to users, tasks, and organization as opposed to transitory conversational contexts.
• Status Management: Monitor and manage ongoing conditions, including artifacts and procedural logs.
• Self-Review Mechanisms: Employ techniques for error reduction through self-evaluation or second-look validation.
• Collaborative Agent Design: Architect multi-agent systems with specialized functionalities and managed interactions.
• Human Oversight: Integrate human verification for low-confidence scenarios and maintain accessible review processes.
• Operational Safeguards: Implement restrictions and checks to control tool usage and sensitive data handling.
• System Transparency: Maintain clear logs of operations, failures, and performance metrics for system observability.
Principal Duties:
• API Engineering: Conceptualize, program, validate, and disseminate robust REST APIs using Python’s FastAPI framework.
• Web Application Integration: Partner with frontend developers to create seamless app-API interactions.
• CI/CD Stewardship: Construct and refine GitHub Actions and Azure DevOps-based automation for swift and precise code deployment.
• Security-First Development: Apply advanced security practices, including OAuth2 and JWT, in web applications and APIs.
• Code Integrity & Evaluation: Produce maintainable, well-documented code and participate in comprehensive testing and review procedures.
• Knowledge Documentation & Teamwork: Commit to thorough documentation practices and continuous collaboration with multiple departments.