About the Role
In this role you will architect and deploy the orchestration layer that coordinates interactions between vendor AI and internal multi agent systems and human participants to improve how users get help. You will build production grade Python services that bridge advanced ML AI research with reliable customer facing products. You will lead end to end project execution for complex ML initiatives, managing priorities, technical trade offs, and cross functional dependencies from design through delivery. You will establish best practices for system design, coding standards, and AI ML development workflows across the organization. You will mentor engineers on architectural integrity and modern AI ML patterns, raising the technical bar for the broader organization. You will conduct design reviews to ensure every feature meets standards for security, scalability, and performance.
Requirements
- 5+ years of professional experience in machine learning and software engineering with a track record of shipping production grade ML services at scale
- Hands on expertise building with modern AI architectures LLMs deep learning and the generative AI ecosystem including frameworks such as LangGraph LangSmith Google ADK Vertex AI or AWS Bedrock
- Deep proficiency in Python with demonstrated ability to write clean maintainable highly tested production code
- Specialized knowledge in at least one domain NLP information retrieval computer vision or advanced statistical modeling
- Proven ability to write technical design documents and present ML system architectures to cross functional stakeholders translating complex technical concepts for non technical audiences
- Utilizes generative AI responsibly maintaining human oversight to deliver business ready outputs and drive measurable improvements in workflow efficiency cost and quality
Responsibilities
- Architect and deploy the orchestration layer that manages state transitions context sharing and intent routing across vendor and internal LLM frameworks in a distributed conversational environment
- Build production grade Python services that bridge advanced ML AI research with reliable customer facing products
- Lead end to end project execution for complex ML initiatives managing priorities technical trade offs and cross functional dependencies from design through delivery
- Establish best practices for system design coding standards and AI ML development workflows across the organization
- Mentor engineers on architectural integrity and modern AI ML patterns raising the technical bar for the broader organization
- Conduct design reviews to ensure every feature meets standards for security scalability and performance
Benefits
- Equity
- Bonus eligibility
- Medical dental and vision benefits