Senior Full Stack Developer
New
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Enterprise KnowledgeEnterprise Software, AI
While local candidates are preferred, we are also able to hire remote candidates residing in the following states: CO, FL, MA, NC, NH, NM, NY, OR, PA, RI, TX, and WA.Full-TimeSenior
Salary140,000 - 155,000 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonSQLAgileGitJavaTypeScriptGoReactGitHub ActionsGenerative AI
Requirements
- Bachelor's degree in Computer Science, Data Science, Math, or a related technical field
- 8+ years of professional software development experience
- Demonstrated experience leading projects or workstreams and mentoring other engineers
- Deep proficiency in Python (preferred), Golang, or Java for backend development
- Extensive experience with modern JavaScript frameworks (e.g., React, TypeScript)
- Strong background in data modeling, database architecture, and SQL
- Proven experience with code versioning tools (Git) and CI/CD (GitHub Actions)
- Proficiency in using Generative AI tools to accelerate the full Software Development Life Cycle
- Demonstrated ability to lead technical teams, facilitate client meetings, and present work products directly to senior client stakeholders
Responsibilities
- Lead development on client projects, setting technical direction, making architectural and system design decisions, and ensuring delivery quality across the team
- Design, implement, and maintain scalable backend microservices (Python) and intuitive frontend interfaces (React/Vue) for AI-driven applications
- Own the design of complex system components end-to-end and communicate that design clearly to both technical and non-technical clients
- Mentor and coach junior and mid-level developers, conducting code reviews, providing technical guidance, and helping grow team capabilities
- Design, maintain, and implement solutions that adhere to security, access controls, scalability, and other constraints
- Lead design and implementation of agentic AI solutions, including orchestration patterns, tool use, and memory/retrieval integration
- Architect end-to-end Retrieval Augmented Generation (RAG) workflows, including retrieval pipeline architecture, embedding strategies, and response evaluation
- Serve as a trusted technical advisor to data subject matter experts and business users
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