AI Engineer - W2 Only

Role : AI Engineer

Location: New York, NY
Job Type: Contract
Employment Type: W2 OnlyJob Summary

We are looking for an experienced AI Engineer to join our team in New York. The ideal candidate will have strong hands-on experience building and deploying AI/ML solutions, working with Generative AI, LLMs, APIs, and modern cloud technologies.

Key Responsibilities

• Design, develop, and deploy AI/ML solutions for enterprise applications.
• Build and integrate Generative AI and LLM-based applications.
• Develop AI agents, RAG pipelines, prompt engineering, and LLM orchestration workflows.
• Work with structured and unstructured data for AI-driven solutions.
• Develop and integrate REST APIs and AI services into existing applications.
• Implement model evaluation, monitoring, testing, and optimization.
• Collaborate with data scientists, software engineers, product teams, and business stakeholders.
• Ensure AI solutions meet security, scalability, reliability, and performance requirements.
• Troubleshoot and optimize AI/ML applications in production environments.

Required Skills

• Strong experience in AI/ML Engineering and software development.
• Hands-on experience with Generative AI, LLMs, and RAG.
• Strong programming experience with Python.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
• Experience working with OpenAI, Azure OpenAI, Anthropic, Gemini, or other LLM APIs.
• Strong understanding of prompt engineering, embeddings, vector databases, and semantic search.
• Experience developing and consuming REST APIs.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with Git, CI/CD, Docker, and modern software development practices.
• Strong problem-solving and communication skills.

Preferred Skills

• Experience building AI Agents / Agentic AI solutions.
• Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search.
• Knowledge of ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience with Kubernetes and containerized AI workloads.
• Knowledge of AI security, governance, responsible AI, and model observability.
• Experience working in enterprise environments.