Full-Stack AI Engineer jobs in United States
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Talentsearchpro ยท 1 day ago

Full-Stack AI Engineer

Talentsearchpro is seeking a highly skilled Full-Stack AI Engineer with at least 5 years of professional experience. The ideal candidate will design and deploy AI agent infrastructure and features at scale, contributing across the stack from frontend interfaces to backend APIs.

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Responsibilities

Design, develop, and maintain frontend applications using React and Next.js
Build, test, and deploy backend services and APIs (Python/Django/FastAPI preferred, but other languages/frameworks welcome)
Collaborate with founders, growth team, designers, and other engineers to deliver high-impact features
Ensure scalability, performance, and security across the stack
Implement CI/CD pipelines, automated testing, and monitoring solutions
Contribute to infrastructure planning, deployment, and optimization in cloud environments (AWS, GCP, or Azure)
Develop and deploy AI-powered features in production, including RAG (Retrieval-Augmented Generation) systems, multi-agent infrastructure, and evaluation frameworks (Evals)
Build real-world AI use cases by integrating fine-tuned models and large language model APIs into user-facing products
Create data pipelines for AI model training, evaluation, and continuous improvement
Mentor junior developers and promote engineering best practices

Qualification

ReactPythonAI applicationsNext.jsCloud infrastructureCI/CD pipelinesDockerKubernetesTask queuesGitNoSQL databasesRedisRAG pipelinesModel fine-tuningLLM evaluation

Required

5+ years of professional software engineering experience
Proven experience with React and Next.js in production environments
Strong backend development skills (Python preferred)
Solid understanding of relational and/or NoSQL databases
Experience with Git and collaborative development workflows
Knowledge of cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines
Experience implementing background workers and task queues (Celery, RQ, etc.)
Proficiency with Redis for caching, pub/sub, or job queues
Hands-on experience building and deploying AI applications in production environments
Experience implementing RAG pipelines, AI agent orchestration, model fine-tuning, and performance monitoring
Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety

Company

Talentsearchpro

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Talent Search Pro, we understand that making the right hire is a critical action that you have to take as an organization.

Funding

Current Stage
Early Stage
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