AI Engineer (Lead) - Only W2

Role

• AI Engineer (Lead)

Location

• Remote (US)

Employment Type

• W2 Contract

Length

• 6 months with extension

Visa

• Independent canddiates are preferred (Only W2) - No C2C

Description

• Client is seeking an experienced AI Engineer to drive the transformation of AI initiatives into production-ready, enterprise-scale solutions.
• This role will focus on Agentic AI systems and will work closely with client's AI, engineering and product teams.

Responsibilities

• Design, build, and deploy full stack applications using current stack (Python + React) while remaining language-agnostic.
• Architect secure, scalable systems with a strong emphasis on security, compliance, and best practices.
• Lead and contribute to internal AI initiatives, including:
  • Supporting existing AI-enabled products.
  • Designing and implementing new AI-driven solutions.
  • Providing internal consulting on how teams can leverage AI.
• Use and evaluate a diverse set of AI developer tools (GitHub Copilot, Cursor, Claude).
• Serve as a technical thought partner to business units to identify opportunities where AI can improve efficiency, reduce risk, or enhance customer experience.
• Ensure all solutions meet security, compliance, and regulatory expectations, particularly in complex environments such as financial services.
• Build and integrate agentic systems powered by cutting‑edge LLM and GenAI technologies.
• Work closely with AI Engineers to turn AI capabilities into production-ready enterprise solutions.
• Design, develop, and deploy agentic AI systems leveraging LLMs and modern AI frameworks.
• Integrate GenAI models into full‑stack applications and internal workflows.
• Collaborate on prompt engineering, fine‑tuning, and evaluation of generative outputs.
• Optimize AI inference pipelines for scalability, latency, and cost efficiency.

Required Skills & Qualifications

• 7+ years of full stack development experience using programming languages like Python, JavaScript, Node.js, ReactJS.
• Experience with LLM frameworks, (LangChain, Bedrock Data Automation).
• Understanding of Git, CI/CD, DevOps, and production‑grade GenAI deployment practices.
• Working experience in Data Processing, AI‑enabled workflows using Python.
• Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI.
• Deep understanding of LLMs, embeddings, vector databases.
• Experience with Docker, Kubernetes, and cloud‑native deployment practices.
• Knowledge of AI observability, model monitoring, and cost optimization strategies.

Nice to Have

• Experience in financial services, especially with core banking systems or other highly complex, regulated domains.
• Deep familiarity with modern AI development patterns, prompt engineering, vector databases, embeddings, or retrieval pipelines.
• Experience with LLM orchestration, prompt management, and evaluation frameworks.
• Knowledge of data governance, security, and compliance in enterprise environments.