Title: Lead AI Engineer/Architect

Location:- Remote

Duration: 06 Months

Visa: US Citizen, GC and GC-EAD

Interview- rounds: Virtual

Need LinkedIn with Photo and Location on LinkedIn| Excellent comms. Required| Small write up | Payment term is net 90

Job Description:

We're needing a Lead AI Engineer who has experience with architecture and design, working w/ multiple engineering teams to design solutions to develop frameworks across a portfolio.

Cloud: GCP, Azure

AI: Must know how to build custom models, how to implement and define those models. Building data pipelines, etc. Heavy Data Analytics background (python).

GenAI: AgenticAI

Must have a Healthcare background. HC + retail would be a huge plus.

Must have Lead experience mentoring other team members and include on resume how many team members they lead in each project - also include if offshore and offshore

100% remote

osition Overview:

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.

Required Qualifications:

·  Proven expertise in AI technologies and frameworks.