Full Stack Generative AI Developer

Position Overview

We are seeking a Full Stack Generative AI Developer to design, build, and prototype end-to-end applications and Proofs of Concept (PoCs) as part of our Software Development team based in Woodlawn, MD. This is a permanent role expected to be onsite 5 days a week.

Key Responsibilities

• Collaborate with stakeholders to understand and refine customer-provided use cases for Generative AI solutions.
• Design, develop, and implement end-to-end Proofs of Concepts (PoCs) using Azure AI and AWS Bedrock.
• Build and maintain scalable, secure, and robust web applications, integrating Generative AI models and APIs.
• Develop both front-end and back-end components, ensuring seamless user experience and data processing.
• Rapidly prototype and iterate on application features based on feedback and evolving requirements.
• Integrate cloud services and manage deployment pipelines for PoC applications.
• Document technical designs, development processes, and application architecture for knowledge sharing.
• Collaborate with data scientists, UI/UX designers, and project managers, to deliver high-quality solutions.
• Conduct code reviews, testing, and debugging to ensure application reliability and performance.
• Stay current with emerging technologies and best practices in Generative AI and full stack development.

Required Qualifications

• Master's +5 years, Bachelor's +7 years, or 13+ years of relevant experience.
• 5+ years of experience in full stack development, including both front-end and back-end technologies.
• 3+ years of experience writing clean, modern Python and utilizing Python web frameworks.
• Hands-on experience with AWS and Azure cloud platforms, including Azure DevOps build and test automation.
• Deep understanding of GenAI and RAG concepts, with experience integrating APIs (Azure OpenAI, AI Search, Azure Vision).
• Proficient in modern Python, language best practices, and backend web frameworks for API development.
• Skilled in JavaScript/TypeScript (Node.js, React, or Angular) and building/consuming RESTful microservices.
• Experience with containerization (Docker, OpenShift) and CI/CD pipelines (Jenkins, Bitbucket).
• Strong foundation in Agile methodologies, unit testing, debugging, and version control.
• Knowledge of Azure security best practices for handling sensitive data, alongside a commitment to ethical AI (fairness, privacy, transparency).
• Strong problem-solving and teamwork skills, with the ability to explain complex AI concepts to non-technical stakeholders.

Preferred Qualifications

• Familiarity with the Azure OpenAI API for natural language processing (NLP) and generative modeling.
• Mastery of Azure ML, Cognitive Services, Databricks, and Synapse, with the ability to combine them with Azure OpenAI for scalable enterprise solutions.
• Hands-on experience deploying GenAI models to production on Azure, utilizing containerization, orchestration, monitoring, and robust security frameworks.
• Familiarity with Python data tools like Jupyter, Pandas, and PyTorch is a strong plus.
• Strong understanding of CI/CD best practices to accelerate production releases.
• Awareness of emerging Generative AI trends and modern Pythonic implementations.
• Ability to preprocess, clean, and manipulate data for RAG ingestion.
• Proficiency in C# and Java.