AI Tech Lead with Python Background

Job Title: AI Technical Lead with Python

Location: Mclean, VA (onsite)

Job Description:

We are seeking an experienced AI Technical Lead with strong expertise in Python, Generative AI, Machine Learning, and Large Language Models (LLMs) to lead the design and development of AI-driven solutions. The ideal candidate will have hands-on experience building scalable AI applications, mentoring development teams, and delivering enterprise-grade AI solutions on cloud platforms.

Key Responsibilities:

Lead the architecture, design, and development of AI/ML and Generative AI solutions using Python.

Design and implement scalable AI applications leveraging LLMs, RAG architectures, and AI agents.

Develop REST APIs and microservices using FastAPI, Flask, or Django.

Build data processing pipelines using Pandas, NumPy, PySpark, and SQL.

Implement Retrieval-Augmented Generation (RAG) using vector databases such as Pinecone, FAISS, ChromaDB, or Milvus.

Integrate AI models from OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, or AWS Bedrock.

Develop prompt engineering strategies to improve LLM performance and reduce hallucinations.

Build and optimize AI pipelines using LangChain, LangGraph, LlamaIndex, or AutoGen.

Collaborate with data scientists, product managers, and business stakeholders to define AI solutions.

Lead code reviews, establish coding standards, and mentor development teams.

Deploy AI applications using Docker, Kubernetes, and CI/CD pipelines.

Monitor AI model performance and implement model evaluation frameworks.

Ensure AI applications follow security, governance, and responsible AI best practices.

Drive technical discussions, architecture reviews, and project planning.

Required Skills

10+ years of software development experience.

5+ years of Python development experience.

3+ years of experience in AI/ML and Generative AI.

Strong programming skills in Python.

Experience with FastAPI, Flask, or Django.

Hands-on experience with LLMs such as GPT-4, Claude, Llama, Gemini, or Mistral.

Experience implementing RAG architectures.

Strong knowledge of LangChain, LangGraph, LlamaIndex, or AutoGen.

Experience with vector databases (Pinecone, ChromaDB, FAISS, Weaviate, Milvus).

Strong understanding of Machine Learning and Deep Learning concepts.

Experience with TensorFlow, PyTorch, or Scikit-learn.

Strong SQL and database design experience.

Experience with REST APIs and microservices.

Experience with Git, GitHub, Jenkins, Azure DevOps, or GitLab CI/CD.

Strong debugging and performance optimization skills.

Cloud Experience

AWS (SageMaker, Bedrock, Lambda, ECS, EKS, S3)

Azure (Azure OpenAI, Azure ML, AKS)

Google Cloud Platform (Vertex AI, Cloud Run)