Overview
Skills
Job Details
Must Have Qualifications: Angular, Python, and microservices architecture
Location: McLean, VA (Onsite 5 days a week, Monday Friday)
Assignment Type: Contract Only
Schedule: Standard Business Hours
Interview Process Format: 1 Round
Type: In-Person Interview
About the Role
We are seeking a Full Stack Python GenAI Developer to support the build and deployment of production-ready applications in partnership with our Data Science team. This role requires strong expertise in Angular, Python, and Microservices architecture, with the ability to integrate and deploy solutions using AWS EKS and existing CI/CD pipelines.
The ideal candidate will have hands-on experience building scalable applications, deploying Microservices, and working closely with Data Scientists to productionize GenAI-driven solutions.
Key Responsibilities
Develop and deploy Python-based Microservices using frameworks such as Flask (or other Python frameworks).
Work with Jenkins-based CI/CD pipelines for deployment on AWS EKS (no need to build pipelines).
Build responsive Angular front-end applications and integrate with backend services.
Partner with Data Scientists to transform their solutions into production-ready applications.
Work with LLM frameworks (e.g., LangChain, LangGraph) for AI-driven applications and Agentic workflows.
Integrate services with knowledge bases, AWS Bedrock, and Azure OpenAI through APIs and wrappers.
Ensure compliance with governance and DevSecOps processes (Fortify, security scans, etc.).
Contribute to building GenAI-based applications and agents.
Must-Have Qualifications
Strong hands-on experience with Angular (latest version preferred).
Proficiency in Python Backend development and Microservices architecture.
Experience deploying applications on AWS EKS using Jenkins-based CI/CD pipelines.
Understanding of DevSecOps practices and secure deployment processes.
Ability to work closely with Data Scientists to build and productionize AI/ML solutions.
Nice-to-Have Qualifications
Experience with GenAI frameworks such as LangChain, LangGraph, or similar.
Familiarity with AWS Bedrock, Azure OpenAI, and knowledge base integrations.
Prior exposure to building GenAI applications or agents.
Experience with containerization and Kubernetes fundamentals.