AI Full Stack Tech Lead

Job Description: We are seeking an experienced AI Technical Lead with deep expertise in Large Language Models (LLMs), Agentic AI, Python, LangChain, LangGraph, RAG architectures, and cloud-based AI platforms. The ideal candidate will lead the design, architecture, development, and delivery of enterprise-scale Generative AI solutions while mentoring engineering teams and driving AI innovation across the organization.

Job Title: AI Full Stack Technical Lead – Generative AI, Agentic AI & LLMs
Location: Tampa, FL ,(Hybrid)
Duration: 6 Months
 
Salary Range: $42.00 - $45.00/Hour on W2 (Without Benefits).
Applicants must be willing to work on W2.
 
Job Description:

• We are seeking an experienced AI Technical Lead with deep expertise in Large Language Models (LLMs), Agentic AI, Python, LangChain, LangGraph, RAG architectures, and cloud-based AI platforms.
• The ideal candidate will lead the design, architecture, development, and delivery of enterprise-scale Generative AI solutions while mentoring engineering teams and driving AI innovation across the organization.

Key Responsibilities:
Technical Leadership:

• Define and drive the AI/GenAI technology roadmap aligned with business objectives.
• Architect scalable, secure, and production-ready AI solutions using modern GenAI frameworks.
• Lead engineering teams in designing and implementing enterprise AI applications.
• Establish coding standards, design patterns, and AI engineering best practices.
• Review solution architectures, code quality, and technical deliverables.
• Provide technical leadership, mentorship, and guidance to the AI development team.

Generative AI & Agentic AI:

• Lead the architecture and development of AI solutions utilizing Python, LangChain, LangGraph, and Agentic AI methodologies.
• Design and implement advanced AI applications leveraging LLMs such as GPT, Claude, Gemini, and Llama.
• Build intelligent autonomous and multi-agent systems using LangGraph, LangChain, CrewAI, AutoGen, or similar frameworks.
• Develop AI agents capable of planning, reasoning, memory management, and tool orchestration.
• Define agent governance, guardrails, evaluation frameworks, and responsible AI controls.

RAG & Knowledge Engineering:

• Design and implement Retrieval-Augmented Generation (RAG) workflows to enhance information retrieval and AI model responses.
• Architect RAG solutions using enterprise knowledge repositories.
• Implement semantic search, vector databases, embeddings, and knowledge graph solutions.
• Optimize prompt engineering, context management, and grounding strategies to improve response quality.

Full-Stack Development:

• Lead the delivery of full-stack applications and mentor engineers.
• Develop backend services and APIs using Python and/or Node.js.
• Build production-quality user interfaces using React and TypeScript.
• Collaborate with cross-functional teams to integrate AI capabilities within existing systems and new products.
• Translate business challenges into innovative AI-powered solutions.

Solution Delivery:

• Drive end-to-end AI solution development from concept and architecture through production deployment.
• Collaborate with business stakeholders, product owners, architects, and engineering teams.
• Drive Agile execution and ensure successful project delivery.
• Ensure quality, performance, robustness, scalability, and reliability of AI systems.

AI Platform & MLOps:

• Manage AI deployment and scalability using cloud services, including Azure AI and AWS Bedrock.
• Establish AI Engineering, LLMOps, and MLOps practices.
• Design CI/CD pipelines for AI applications and model deployment.
• Implement monitoring, observability, model evaluation, and performance tuning.
• Ensure compliance, security, scalability, and reliability of AI systems.
• Ensure best practices in AI model development, data handling, and security compliance.

Team Leadership & Innovation:

• Mentor and guide AI Engineers, ML Engineers, and Software Developers.
• Conduct technical reviews, design sessions, and knowledge-sharing workshops.
• Foster innovation and continuous learning within the AI engineering team.
• Stay abreast of AI research trends and emerging technologies to continuously innovate and improve AI strategies.

Required Qualifications:

• Must have 7+ years of experience in Artificial Intelligence (AI).
• Proven experience leading the delivery of full-stack applications and mentoring engineers.
• Strong hands-on skills in Python and/or Node.js for backend and API development.
• Proficiency in React and TypeScript, including building production-quality user interfaces.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• Extensive experience in AI development with strong Python programming skills.
• Hands-on experience with LangChain, LangGraph, and Agentic AI frameworks.
• Proven expertise in Retrieval-Augmented Generation (RAG) techniques.
• Familiarity with cloud AI services, especially Azure AI and AWS Bedrock.
• Strong problem-solving skills and ability to architect scalable AI systems.
• Excellent communication skills and team leadership experience.
• Experience with containerization and CI/CD pipelines is a plus.