Full Stack Developer

2 weeks ago


Ashburn, VA, United States Dynanet Full time

Dynanet started with a focus on IT infrastructure and operations, helping organizations enhance their networks and overcome the limitations of 1990s technology. From strengthening communication channels to introducing innovative ways to collaborate and share information, Dynanet played a crucial role in shaping the early stages of digital transformation. The companys efforts helped organizations build the very fabric of connectivity that now powers our modern world. Over the last three decades, Dynanet has grown into a trusted partner for organizations looking to innovate boldly and transform seamlessly. While technology continues to evolve and unlock new opportunities, for nearly 30 years, Dynanet remains committed to delivering cutting?edge solutions that drive lasting change for its customers. Through agility, foresight, and an unwavering dedication to excellence, Dynanet continues to empower organizations to thrive in a rapidly changing digital landscape. Our story is more than just a story of technology its a story of vision, growth, and transformation that has shaped the past and continues to pave the way for the future.

About the Role:

Strong experience in modern web development and applied AI integration. The ideal candidate will be comfortable building scalable, data-driven web applications using React, Next.js, NestJS, and MongoDB, and will have hands?on experience implementing Retrieval?Augmented Generation (RAG) systems and prompt engineering for AI?driven features.

Youll work across the stack to design, develop, and deploy robust products that leverage both front?end interactivity and intelligent backend systems.

  • Design, build, and maintain scalable full?stack applications using Next.js, React, NestJS, and MongoDB.
  • Integrate and optimize AI?based features, including RAG pipelines and LLM?powered tools.
  • Develop and tune prompt templates, retrieval chains, and embeddings for contextual AI performance.
  • Collaborate with product managers, designers, and data scientists to translate requirements into technical solutions.
  • Implement secure APIs, efficient data models, and robust backend services.
  • Ensure application performance, security, and reliability across deployments.
  • Participate in code reviews, testing, and CI/CD pipelines.
  • Stay up to date with modern frameworks, AI integration patterns, and best practices in full?stack engineering.
Required Professional Skills:
  • Must have an existing CBP Full BI
Preferred Professional Skills:
  • Familiarity with LangChain, LlamaIndex, or similar frameworks for AI application development.
  • Experience with vector databases (e.g., Pinecone, Weaviate, Milvus).
  • Knowledge of CI/CD pipelines and DevOps practices.
  • Experience working in Agile/Scrum teams.
Dynanet Team Requirements and Expectations:
  • Possess Strong written and verbal communication skills.
  • Highly organized with an ability to prioritize, balance, and effectively advance multiple competing priorities in a high?volume, fast?paced environment.
  • Ability to interact in a professional and collaborative manner with fellow Dynanet Teammates and the clients, and business partners that we work with.
  • Ability and desire to challenge and educate yourself to support and advance IT services delivery in the Federal agencies we serve.
  • Excellent judgment and creative problem?solving skills.
  • Respond to team member and client requests via email, MS teams, or other communication means during core business hours.
  • Active listening skills to understand clients' needs, and collaboration skills to work with other developers and designers.
Education/Experience Requirements:
  • Bachelors degreeinCybersecurity, IT, or related field(orequivalentexperience)
  • Must have an existing CBP Full BI
  • 35 years of experience as a Full Stack Engineer or similar role.
  • Experience building and deploying RAG?based AI systems (e.g., integrating vector databases, embedding models, or LLM APIs).
  • Familiarity with prompt engineering techniques for optimizing AI outputs.
  • Strong understanding of RESTful and GraphQL API design.
  • Experience with version control (Git), containerization (Docker), and cloud platforms (AWS, GCP, or Azure).

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