Full Stack Generative AI Developer

Company Overview

At 4A Consulting, we turn complexity into opportunity. Founded in 2014 and headquartered in Baltimore, MD, we are a women‑owned, boutique consulting firm specializing in delivering innovative, data‑driven solutions to both the Federal Government and Fortune 500 clients. Our team blends deep industry knowledge with advanced technologies to design tailored strategies that drive measurable and sustainable outcomes. We pride ourselves on an agile, collaborative approach that helps organizations navigate challenges and seize emerging opportunities in a rapidly evolving digital landscape.

At 4A, we don’t just deliver projects, we build trusted partnerships that empower our clients to lead with confidence in the digital age.

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. In this role, you will collaborate with cross‑functional teams and stakeholders to translate complex use cases into secure, scalable, and robust AI‑driven solutions using cutting‑edge cloud platforms.

This is a permanent role expected to be onsite 5 days a week.

• 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.

• 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 Dev Ops 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/Type Script (Node.js, React, or Angular) and building/consuming RESTful microservices.
• Experience with containerization (Docker, Open Shift) 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.

• 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.
• Proficien…