Full Stack Developer – AI-Enabled Applications at Advanced Network Consulting Inc

Woodlawn, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Sep, 26

Salary

0.0

Posted On

01 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Full Stack Development, Python, Azure AI, AWS Bedrock, Generative AI, JavaScript, React, Node.js, RESTful APIs, Docker, OpenShift, CI/CD, RAG, FastAPI, Azure OpenAI, Public Trust Clearance

Industry

Description

Description Full Stack Developer – AI-Enabled Applications Work Location: Woodlawn, MD (On-Site, 5 Days/Week) Clearance Requirement: Public Trust (Must Be Obtainable and Maintainable) Position Overview We are seeking an experienced and motivated Full Stack Developer to play a critical, hands-on role in designing, developing, and deploying Generative AI-powered proof-of-concept (PoC) applications in a production environment. The ideal candidate is deeply passionate about AI technologies that benefit society, committed to responsible and ethical AI development, and capable of working across the full technology stack—from cloud infrastructure to user-facing interfaces. Education Requirements • Master's degree with 5+ years of relevant experience, OR • Bachelor's degree with 7+ years of relevant experience, OR • 13+ years of relevant experience in lieu of a degree 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 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 stakeholder feedback and evolving requirements. • Integrate cloud services and manage deployment pipelines for PoC and production applications. • Document technical designs, development processes, and application architecture for knowledge sharing and future reference. • Collaborate cross-functionally with data scientists, UI/UX designers, and project managers to deliver high-quality solutions. • Conduct code reviews, unit testing, and debugging to ensure application reliability, security, and performance. • Stay current with emerging technologies and best practices in Generative AI and full stack development. Basic Qualifications Experience & Technical Foundation • 5+ years of experience in full stack development, including front-end and back-end technologies. • 3+ years of hands-on Python development; comfortable writing clean, efficient, and well-tested code. • Hands-on experience developing and deploying applications on Microsoft Azure and/or Amazon Web Services. • Familiarity with Generative AI concepts and demonstrated experience integrating AI/ML models or APIs into applications. • Proficiency in Python and JavaScript (Node.js, React, or Angular) or similar modern frameworks. • Experience with RESTful APIs, microservices architecture, and containerization technologies (e.g., OpenShift, Docker). • Strong understanding of software development best practices, version control (e.g., Bitbucket), and Agile methodologies. • Excellent problem-solving skills and proven ability to thrive in a collaborative team environment. • Clear, effective communication skills—able to present technical findings and explain complex AI concepts to non-technical stakeholders. Required Skills Azure & AI Expertise • Proficiency in Microsoft Azure services with a focus on AI and ML capabilities, including Azure OpenAI, Azure AI Search, and Azure Vision. • Solid understanding of fundamental AI concepts and Retrieval-Augmented Generation (RAG) for developing generative AI applications. • Commitment to ethical AI development—adhering to principles of fairness, transparency, accountability, and data privacy. • Proficient in Python with familiarity with current best practices and recent language features. • Experience with Python web frameworks for building APIs and backend services (e.g., FastAPI, Flask, Django). • Strong experience implementing and consuming RESTful web services in production environments. • Solid experience with CI/CD practices, including unit testing, continuous integration with tools such as Jenkins, and version control using Bitbucket. • Experience with containerization and orchestration tools such as Docker and OpenShift for deployment and scaling. • Familiarity with Azure DevOps for automating builds, testing, and deployment within Azure environments. • Understanding of compliance and security best practices within Azure, particularly regarding sensitive data such as personal disability information. Preferred / Desired Skills • Familiarity with the Azure OpenAI API and its capabilities for natural language processing (NLP) and generative modeling. • Advanced knowledge of Azure AI services including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Synapse Analytics—particularly in combination with Azure OpenAI frameworks. • Ability to preprocess, clean, and manipulate data for RAG ingestion pipelines. • Hands-on experience deploying Generative AI models into production environments on Azure, including containerization, orchestration, monitoring, and security considerations. • Proficiency in C# and/or Java as supplemental languages. • Experience with CI/CD best practices and DevOps tooling to accelerate quality releases to production. • Familiarity with data science tools, libraries, and frameworks such as Jupyter Labs/Notebooks, pandas, and PyTorch. • Awareness of emerging issues and trends in Generative AI development and Pythonic approaches to leveraging them. Additional Requirements • Must be able to obtain and maintain a Public Trust clearance. • Must be willing and available to work on-site in Woodlawn, MD, five (5) days per week. • Must be authorized to work in the United States.

Responsibilities

Design and deploy Generative AI-powered proof-of-concept applications using Azure AI and AWS Bedrock. Develop end-to-end web applications, integrating AI models and managing cloud deployment pipelines.