Request ID: 93189-1
Title: Gen AI Tech Lead
Location: Tampa FL
Duration: 6+ Months
Salary Range: $40 - $45 an hour on C2C/W2
Job Description:
As a AI Tech Lead with a focus on AI-driven intelligent systems, you will lead the design, development, and
deployment of advanced NLP and cognitive search solutions using Python, Langchain, LangGraph,
Retrieval-Augmented Generation (RAG), and Agentic AI models.
Key Responsibilities
" Design scalable, maintainable AI solutions that integrate Langchain, LangGraph, and RAG
methodologies to enhance knowledge discovery and conversational AI capabilities.
" Lead development efforts using Python to prototype and productionize AI agents and workflows.
" Collaborate with data engineering and DevOps teams to implement data pipelines and model deployment
strategies.
" Develop and optimize RAG systems combining vector search, knowledge graphs, and LLMs to provide
contextual and accurate responses.
" Architect agentic AI systems that perform autonomous tasks by chaining actions, managing states, and
integrating external APIs.
" Provide technical leadership and architecture guidance for AI and NLP projects.
" Evaluate emerging AI technologies and frameworks to continuously improve solution design.
" Create comprehensive technical documentation and architecture diagrams to facilitate knowledge transfer.
" Ensure solutions meet security, compliance, and performance standards.
.
Required Skills and Qualifications
. " Strong proficiency in Python, with experience in backend or AI service development.
" Hands-on experience with Langchain and/or LangGraph frameworks.
" Deep understanding of Retrieval-Augmented Generation (RAG) systems and techniques.
" Experience designing and implementing agentic AI architectures, autonomous workflows, or
multi-agent systems.
" Familiarity with knowledge graphs, vector search engines (e.g., FAISS, Pinecone, Weaviate),
and LLM integration.
" Solid understanding of NLP concepts, transformer models, and prompt engineering.
" Ability to translate complex business requirements into scalable AI solutions.
" Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker,
" Kubernetes).
" Strong communication skills and ability to collaborate across multidisciplinary teams
Role Descriptions: We are looking for a versatile Lead Full-Stack AI Engineer proficient in backend and frontend development with strong experience in AI/ML technologies. The ideal candidate will work closely with cross-functional teams to develop scalable web applications featuring a Python backend| React-based frontend| and AI/ML-powered functionalities leveraging tools like Scikit-learn| TensorFlow| Azure ML| and Langchain. The role requires a passion for cutting-edge machine learning integrations and delivering high-quality| performant software. AI System Key Responsibilities5+ years of professional software engineering experience| with at least 2 years building LLM-poweredor agentic applications in productionStrong Python skills async/await| type hints| modern tooling (uv| ruff| pyright)Hands-on experience with LangChain| LangGraph| or equivalent agent frameworks youunderstand tool calling| state graphs| checkpointing| and multi-step agent executionExperience designing and operating microservices with async Python web frameworks (FastAPI|Starlette)Solid understanding of relational databases PostgreSQL| schema design| migrations(Alembic/similar)| query optimization| and async ORMs (SQLAlchemy 2.0)Experience with message-driven architectures RabbitMQ| Kafka| or similar broker-based asyncprocessingFamiliarity with vector databases and embeddings building RAG pipelines| semantic search|chunking strategiesWorking knowledge of React and TypeScript able to understand and modify frontend features| notjust consume APIsExperience with Docker| Kubernetes| and CI/CD in cloud environments (Azure preferred)Experience with LLM provider APIs (OpenAI API| or compatible providers) model configuration| streaming responses| token management| and structured outputStrong understanding of prompt engineering system prompts| multi-agent prompt architectures| few-shot patterns| and cost optimizationExperience with MCP (Model Context Protocol) or similar integration protocols building serversthat expose AI capabilities to external platforms| defining tool schemas| and managing async workflowstate
Essential Skills: We are looking for a versatile Lead Full-Stack AI Engineer proficient in backend and frontend development with strong experience in AI/ML technologies. The ideal candidate will work closely with cross-functional teams to develop scalable web applications featuring a Python backend| React-based frontend| and AI/ML-powered functionalities leveraging tools like Scikit-learn| TensorFlow| Azure ML| and Langchain. The role requires a passion for cutting-edge machine learning integrations and delivering high-quality| performant software. AI System Key Responsibilities5+ years of professional software engineering experience| with at least 2 years building LLM-poweredor agentic applications in productionStrong Python skills async/await| type hints| modern tooling (uv| ruff| pyright)Hands-on experience with LangChain| LangGraph| or equivalent agent frameworks youunderstand tool calling| state graphs| checkpointing| and multi-step agent executionExperience designing and operating microservices with async Python web frameworks (FastAPI|Starlette)Solid understanding of relational databases PostgreSQL| schema design| migrations(Alembic/similar)| query optimization| and async ORMs (SQLAlchemy 2.0)Experience with message-driven architectures RabbitMQ| Kafka| or similar broker-based asyncprocessingFamiliarity with vector databases and embeddings building RAG pipelines| semantic search|chunking strategiesWorking knowledge of React and TypeScript able to understand and modify frontend features| notjust consume APIsExperience with Docker| Kubernetes| and CI/CD in cloud environments (Azure preferred)Experience with LLM provider APIs (OpenAI API| or compatible providers) model configuration| streaming responses| token management| and structured outputStrong understanding of prompt engineering system prompts| multi-agent prompt architectures
Appreciate your quick response and please feel free to reach me out for any query you may have.
Thanks