Job Title: Full Stack AI Engineer AI/ML Implementation

Job ID: 118218-40-4 / 118218-40-2
Location: Remote
Employment Type: Contract
Experience: 4 6 Years
Rate: $50/hour (slightly flexible for strong candidates)

Work Authorization & Education Requirements

• Work Authorization: Candidates must be legally authorized to work in the United States without current or future employer sponsorship. USC candidates preferred.

• Education: Bachelor's degree or higher from an accredited U.S. college, university, or recognized educational institution.

• Preference: Strong academic background from a reputable institution.

• Role Summary

  We are seeking a Full Stack AI Engineer with strong hands-on experience in Python, Machine Learning, Deep Learning, Generative AI, and cloud-based application development. The ideal candidate must demonstrate AI-assisted coding (Vibe Coding), Claude/Claude Code, RAG, Agentic AI, and strong traditional coding fundamentals.

  The candidate will design, develop, deploy, and maintain production-ready AI solutions using Python, TensorFlow/PyTorch, LLMs, Azure services, and modern software engineering practices. Experience using AI coding tools such as Claude Code and Cursor alongside Git-based workflows and CI/CD pipelines is essential.

  Key Responsibilities

• Design, develop, train, evaluate, and deploy machine learning and deep learning models for classification, regression, ranking, computer vision, NLP, and time-series use cases.

• Build LLM-powered applications using Anthropic Claude, Azure OpenAI, OpenAI, or equivalent models.

• Design and implement Retrieval-Augmented Generation (RAG) solutions, including document chunking, embeddings, vector databases, and reranking.

• Develop Agentic AI workflows with tool calling, orchestration, guardrails, evaluation frameworks, and human-in-the-loop review.

• Apply prompt engineering, fine-tuning, structured outputs, and model evaluation techniques.

• Build and maintain data and feature pipelines on Azure, ensuring data quality, lineage, and reproducibility.

• Implement MLOps practices, including model versioning, automated retraining, drift detection, monitoring, and rollback strategies.

• Use AI-assisted development tools such as Claude Code and Cursor alongside traditional coding practices, ensuring the quality and security of AI-generated code.

• Manage source code using Git, branching strategies, pull requests, and code reviews.

• Build and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, or equivalent tools.

• Deploy and operate AI services on Azure using Docker, Kubernetes/AKS, and infrastructure-as-code tools such as Terraform or Bicep.

• Implement logging, tracing, evaluation, and monitoring to manage AI quality, latency, reliability, and cost.

• Address security, compliance, data privacy, PHI/PII protection, prompt injection, and model risks.

• Collaborate with product, scientific, and business stakeholders to translate business needs into effective AI solutions.

• Participate in technical design reviews, code reviews, and knowledge sharing while promoting reliable, secure, and observable AI systems.

• Required Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field.

• 4+ years of software engineering experience, including at least 2 years building and deploying production AI/ML solutions.

• Strong Python programming skills and experience with TensorFlow and/or PyTorch, scikit-learn, pandas, and NumPy.

• Hands-on experience developing and deploying LLM applications using Claude/Anthropic, Azure OpenAI, OpenAI, or open-source models.

• Practical experience with RAG, embeddings, vector databases, and retrieval optimization.

• Experience developing Agentic AI workflows, tool calling, prompt engineering, and AI evaluation.

• Demonstrated proficiency with AI-assisted coding/Vibe Coding tools, especially Claude Code and Cursor, along with strong manual coding skills.

• Strong Git fundamentals, branching strategies, pull requests, and code reviews.

• Experience building and maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools.

• Hands-on Azure deployment experience with AKS, App Service, Azure Functions, Azure AI/ML services, or equivalent.

• Experience with Docker and containerized application deployment.

• Understanding of MLOps, monitoring, observability, model quality, and production troubleshooting.

• Excellent written and verbal communication skills, with the ability to explain technical concepts and trade-offs to non-technical stakeholders.

• Ability to work effectively in a fully remote, globally distributed team.

• Interview Requirements

• Strong technical competency in AI/ML, Generative AI, Python, and software engineering.

• Ability to explain technical concepts clearly and confidently.

• Strong communication skills for client-facing discussions.

• Successful completion of both technical and communication assessments/interviews.