Senior Lead AI Developer
- SHIRO Technologies LLC
7 Days Ago
NA
NA
Scottsdale-AZ
8-12 Years
Required Skills: AI Technologies and frameworks, Full Stack Python development, Designing and deploying GenAI application using RAG architecture, MongoDB Atlas, AI/ML models, Azure, GCP, AgenticAI and MCP Technologies
Job Description
We are seeking a highly skilled and experienced Senior Lead AI Developer to join our dynamic team. The ideal candidate will be an expert in AI technologies, with a strong background in full stack Python development, GenAI application design, and document processing pipelines. You will lead and manage development tasks, coordinate with cross-functional teams, and drive the successful delivery of cutting-edge AI solutions in a production environment.
Key Responsibilities:
Lead the design, development, and testing of full stack (frontend, backend, API) Python applications.
Design and implement GenAI applications using Retrieval-Augmented Generation (RAG) in production settings.
Build and optimize document ingestion pipelines and document processing workflows utilizing vector databases (e.g., MongoDB Atlas).
Manage and coordinate development tasks, collaborating with internal and external teams to ensure project success.
Oversee the full software development lifecycle, delivering high-quality solutions with minimal supervision.
Design and develop AI/ML models for data analytics, prediction, and forecasting.
Deploy and maintain AI applications on cloud platforms such as Azure and Google Cloud Platform (GCP).
Integrate and leverage AgenticAI and MCP technologies in AI solutions.
Communicate effectively with technical and non-technical stakeholders, providing clear updates and documentation.
Key Responsibilities:
Lead the design, development, and testing of full stack (frontend, backend, API) Python applications.
Design and implement GenAI applications using Retrieval-Augmented Generation (RAG) in production settings.
Build and optimize document ingestion pipelines and document processing workflows utilizing vector databases (e.g., MongoDB Atlas).
Manage and coordinate development tasks, collaborating with internal and external teams to ensure project success.
Oversee the full software development lifecycle, delivering high-quality solutions with minimal supervision.
Design and develop AI/ML models for data analytics, prediction, and forecasting.
Deploy and maintain AI applications on cloud platforms such as Azure and Google Cloud Platform (GCP).
Integrate and leverage AgenticAI and MCP technologies in AI solutions.
Communicate effectively with technical and non-technical stakeholders, providing clear updates and documentation.
Required Qualifications:
Proven expertise in AI technologies and frameworks.
Extensive experience in full stack Python development (frontend, backend, API).
Demonstrated success in designing and deploying GenAI applications using RAG architecture in production and hands-on experience building document ingestion pipelines with vector databases (MongoDB Atlas preferred).
Strong leadership skills with experience managing development tasks and coordinating teams.
Excellent verbal and written communication skills.
Ability to lead projects independently with minimal supervision.
Solid background in data analytics, prediction, and forecasting using AI/ML models.
Experience deploying AI applications to cloud platforms (Azure, GCP).
Familiarity with AgenticAI and MCP technologies.
Proven expertise in AI technologies and frameworks.
Extensive experience in full stack Python development (frontend, backend, API).
Demonstrated success in designing and deploying GenAI applications using RAG architecture in production and hands-on experience building document ingestion pipelines with vector databases (MongoDB Atlas preferred).
Strong leadership skills with experience managing development tasks and coordinating teams.
Excellent verbal and written communication skills.
Ability to lead projects independently with minimal supervision.
Solid background in data analytics, prediction, and forecasting using AI/ML models.
Experience deploying AI applications to cloud platforms (Azure, GCP).
Familiarity with AgenticAI and MCP technologies.
