5+ years in full stack development, both front-end and back-end.
3+ years of Python programming experience.
Proficient in languages like JavaScript, with experience in Node.js, React, or Angular.
Familiar with RESTful APIs, microservices, and containerization tools like OpenShift or Docker.
Strong grasp of software best practices and agile methodologies. Sought after is experience with Microsoft Azure and AWS.
Responsibilities
Collaborate with stakeholders to refine Generative AI use cases.
Design and implement end-to-end Proofs of Concept using Azure and AWS.
Build scalable web applications that integrate Generative AI models.
Develop both front-end and back-end components for seamless user experience.
Rapidly prototype and iterate application features based on user feedback.
Document technical designs and collaborate across teams for quality solutions.
Conduct code reviews and stay current with trends in AI and full stack development.
Benefits
Opportunity to work with cutting-edge Generative AI technologies.
Collaborative team environment with cross-functional interactions.
Engagement with a variety of stakeholders across projects.
Potential for career growth in a rapidly evolving field.
On-site work provides direct collaboration and team synergy.
Full Job Description
Position Description
Generative AI Solution Development
Collaborate with stakeholders to understand and refine customer-provided use cases for Generative AI solutions.
Design, develop, and implement end-to-end Proofs of Concept (PoCs) using Azure AI and AWS Bedrock platforms.
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 efficient data processing.
Rapidly prototype and iterate on application features based on feedback and evolving requirements.
Cloud & Application Deployment
Integrate cloud services and manage deployment pipelines for PoC applications.
Documentation & Collaboration
Document technical designs, development processes, and application architecture for knowledge sharing and future reference.
Collaborate with cross-functional teams, including data scientists, UI/UX designers, and project managers, to deliver high-quality solutions.
Quality & Continuous Improvement
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.
Skills Requirements Foundation for Success (Basic Qualifications)
Full Stack & Software Development
5+ years of experience in full stack development, including both front-end and back-end technologies.
3+ years of experience in Python development. You should be comfortable writing clean, efficient code.
Proficiency in programming languages such as Python, JavaScript (Node.js, React, or Angular), or similar technologies.
Experience with RESTful APIs, microservices architecture, and containerization (e.g., OpenShift or Docker).
Strong understanding of software development best practices, version control (e.g., Bitbucket), and agile methodologies.
Cloud & AI Experience
Hands-on experience developing applications using cloud platforms such as Microsoft Azure and/or Amazon Web Services.
Familiarity with Generative AI concepts and experience integrating AI/ML models or APIs into applications.
Professional Skills
Excellent problem-solving skills and ability to work collaboratively in a team environment.
Clear and effective communication skills are necessary for collaborating with team members, presenting findings, and explaining complex AI concepts to non-technical stakeholders.
Factors To Help You Shine (Required Skills)
Required Conditions
Selected candidate must be able to obtain and maintain a public trust clearance
Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week
Master's and 5+ years of experience, Bachelor's and 7+ years of experience or 13+ years in lieu of a degree
Azure AI & Generative AI
Proficiency in utilizing Microsoft Azure services, with a focus on AI and ML services such as Azure OpenAI, Azure AI Search, and Azure Vision.
Understanding of fundamental AI and RAG concepts for developing generative AI applications.
Commitment to ethical AI development, ensuring adherence to principles like fairness, transparency, accountability, and privacy in AI applications.
Python & API Development
Proficient in Python and familiar with current best practices and recent language features.
Experience with Python web frameworks for building APIs and backend services.
Strong experience in implementing and consuming RESTful web services.
DevOps & Software Engineering
Solid experience with software development best practices, including unit testing, continuous integration with tools like Jenkins, and version control with Bitbucket.
Experience with containerization and orchestration tools like Docker and OpenShift will be beneficial for deployment and scaling applications.
Familiarity with Azure DevOps for automating builds, testing, and deployment processes within Azure.
Security & Compliance
Understanding of compliance and security best practices within Azure, especially concerning handling sensitive data such as personal disability information.
How To Stand Out From The Crowd (Desired Skills)
Advanced Azure AI Expertise
Familiarity with the Azure OpenAI API and its capabilities for natural language processing (NLP) and generative modeling is highly desirable.
Mastery of Azure AI services beyond the basics, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Synapse Analytics, would make you a valuable asset. This includes understanding how to leverage these services in combination with Azure OpenAI frameworks for enhanced functionality and scalability.
RAG & Data Preparation
Ability to preprocess, clean, and manipulate data for RAG ingestion.
Production AI Deployments
Hands-on experience deploying generative AI models into production environments on Azure infrastructure is highly desirable. Understanding deployment considerations such as containerization, orchestration, monitoring, and security ensures smooth integration of AI solutions into real-world applications.
Additional Technical Skills
Proficiency in C# and Java.
Delivery (CI/CD) best practices and use of DevOps to accelerate quality releases to Production.
Familiarity with data science tools, libraries, and frameworks (e.g., Jupyter Labs/Notebooks, pandas, PyTorch) is a strong plus.
Awareness of issues and trends in Generative AI and Pythonic use of these is desirable.
