Application Programming Interface (API), Architectural Services, Artificial Intelligence (AI), Code Reviews, Continuous Improvement, Data Structures, Design Patterns Programming Methodologies, Distributed Computing, GraphQL, Identify Issues, Internet Application, Java, Node.js, Open Source, Performance Management, Privacy Controls, Product Design, Python Programming/Scripting Language, Quality Management, REST (Representational State Transfer), React.js, Scalable System Development, Software Development, Software Engineering, Systems Reliability, Test Design, Test Patterns, Use Cases, User Interface/Experience (UI/UX)
Full Stack AI Engineer
Remote
Rate: $60/hr on C2C
Indent: PSL213709_1-219-1
Full Stack AI Engineer who can design, build, and operate end to end, AI powered applications. This role blends strong full stack engineering fundamentals with hands on experience applying modern AI/ML and LLM technologies in production systems. You will work across frontend, backend, and AI layers to deliver scalable, secure, and user centric solutions—owning features from concept to production and continuously improving them using data and feedback.
Required Qualifications
• Strong experience in full stack software development
• Proficiency in frontend technologies (e.g., React, Angular, or similar)
• Proficiency in backend development (e.g., Node.js, Python, Java, or similar)
• Hands on experience building or integrating AI/ML or LLM based solutions
• Experience with APIs, databases, and distributed systems
• Solid understanding of software engineering fundamentals (data structures, APIs, testing, design patterns)
Full Stack Engineering
• Design, build, and maintain end to end web applications using modern frontend and backend frameworks
• Develop scalable backend services and APIs (REST / GraphQL) to support AI driven use cases
• Ensure high standards for performance, reliability, security, and maintainability
• Write clean, testable, well documented code and participate in code reviews
AI / ML & LLM Development
• Design and implement AI powered features, including LLM based workflows, retrieval augmented generation (RAG), agents, and prompt driven systems
• Integrate AI models into applications using APIs and SDKs (open source or enterprise approved)
• Collaborate on model evaluation, prompt tuning, and experimentation to improve quality and accuracy
• Apply responsible AI principles, including security, privacy, explainability, and bias mitigation
Cloud, DevOps & Production Readiness
• Deploy and operate applications in cloud environments using CI/CD pipelines
• Monitor application and AI system performance, reliability, and cost
• Troubleshoot production issues across frontend, backend, and AI components
Collaboration & Ownership
• Partner with product managers, designers, and other engineers to translate business needs into technical solutions
• Contribute to architectural decisions and technical standards
• Mentor junior engineers and promote best practices across the team