Provide technical leadership for design, architecture, and implementation of AI-powered systems
Establish engineering standards and ensure architectural integrity
Guide the development of scalable, secure AI applications
Serve as the primary technical authority for AI initiatives
Collaborate closely with product leadership for performance, reliability, and governance expectations
Operate autonomously and own technical decisions
Design and architect AI-driven applications and enterprise integrations
Lead development of retrieval-augmented generation and LLM-based workflows
Define engineering standards, code quality practices, and review processes
Support monitoring, evaluation, and continuous optimization of deployed models
Balance speed of delivery with architectural soundness
Partner closely with AI Delivery Manager for technical execution alignment with business priorities
Drive hands-on development and ensure delivery of production-ready AI systems

Requirements

Experience delivering AI/ML or data products into production environments
Strong understanding of system architecture (APIs, data pipelines, cloud platforms)
Proven ability to lead technical direction and mentor engineers
Experience building solutions aligned to measurable business outcomes
Experience with Azure AI services, Microsoft AI Foundry (Azure AI Studio), vector databases, or LLM-based systems (preferred)
Familiarity with MLOps practices (preferred)
Experience in consulting or enterprise environments (preferred)

Benefits

Extensive medical coverage
Disability and life insurance coverage
Continuing education benefits
Paid time off
Employee assistance program
Retirement savings plan with company matching contributions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI-powered systemssystem architectureAPIsdata pipelinescloud platformsretrieval-augmented generationLLM-based workflowsMLOps practicescode quality practicesproduction-ready AI systems

Soft Skills

technical leadershipmentoringcollaborationautonomydecision-makingperformance managementreliability managementgovernancecontinuous optimizationbalancing speed and quality