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Principal AI Engineering Lead

IQ Clarity
Full-time
On-site
Austin
Job Description

Job Description

Principal AI Engineering Lead As the

Principal AI Engineering Lead , you will drive the vision, strategy, and execution of our client's AI initiatives. In this role, you'll collaborate with stakeholders across the organization to develop and deliver a strategic roadmap for the AI components of our solutions. You'll lead a team of AI engineers, ensuring alignment with business goals, overseeing deliverables, and contributing directly to the design and implementation of advanced AI systems. You will be both a strategic leader and a hands-on contributor—analyzing performance metrics, incorporating user feedback, and leveraging the latest advancements in AI to continuously enhance our capabilities. As a key technical leader, you will also help scale this division and mentor the next generation of AI talent within the company. Key Responsibilities Lead and coordinate the work of the AI engineering team to deliver high-impact solutions.

Define, implement, and evolve AI capabilities that address complex and unique business challenges.

Ensure the quality, reliability, and scalability of AI systems in production environments.

Partner with stakeholders to develop and execute the strategic AI roadmap.

Evaluate new AI initiatives through cost-benefit and ROI analyses, balancing innovation with practical execution.

Stay current with the latest AI research, tools, and frameworks to drive continuous improvement and innovation.

Provide mentorship and guidance to engineers, fostering a culture of technical excellence and collaboration.

Qualifications & Experience 7+ years of experience in an engineering leadership role (e.g., Lead, Manager, Principal, or similar).

Master's or Ph.D. in Computer Science, ideally with a specialization in Artificial Intelligence or Machine Learning.

Hands-on experience designing and deploying

RAG (Retrieval-Augmented Generation)

and

Agentic

systems.

Deep understanding of

LLMs ,

Deep Learning architectures , and

AI model deployment

in production.

Proficiency in

Python

and experience with tools such as

DSPy ,

MLflow , and

Opik .

Experience with

vector databases

and information retrieval systems.

Strong foundation in

data structures ,

algorithms , and

software engineering principles .

Demonstrated ability to stay abreast of emerging AI methodologies and apply them effectively.

Excellent communication and collaboration skills, with the ability to translate complex technical concepts for non-technical audiences.

Creative problem-solving abilities and adaptability in a fast-paced, evolving environment.