Sr. AI Engineer ( AI Coding ) Contract Local to TX

Location – Mountain View/Dallas, TX. Onsite first preference Locals
Roles – Sr. AI Engineer
Sr level resume: 10+ years of experience.
4 Rounds of technical interviews (Webex)
Visa : H1B ,H4EAD, USC, TN
Rate: $60

Onsite 3 days

Duration: 6 months + Extension
Onsite positions: 2

JD

Responsibilities

Build end-to-end solutions that demonstrate how the latest advances in AI can drive transformative new experiences for our customers.

Collaborate closely with business units and platform teams to accelerate testing and deployment of new technologies and capabilities into Intuit’s products and platforms.

Ensure excellence in data quality, model evaluation, and lifecycle management through rigorous monitoring, testing, and retraining practices.

Champion responsible AI practices, ensuring models are fair, transparent, and trustworthy.

Mentor and grow AI talent, championing a culture of innovation, ethics, and rigor.

Qualifications

Deep technical AI expertise especially in areas like training LLMs, reasoning models, multi-modal models and their application to Forecasting and Planning, Decision Making Under Uncertainty, Multi-objective Optimization, Learning from Human Feedback, Data Cognition, and Deep Personalization to build production-grade scalable AI agents and systems.

8+ years of experience or significant demonstrated impact developing and deploying AI solutions at scale that successfully solve challenging customer problems.

AI Tools Fluency: Hands-on experience using AI coding tools (e.g., Claude Code, Cursor, Codex) to augment and accelerate your daily development workflows.

Experience building large-scale Machine Learning applications on cloud platforms like AWS, GCP, or Azure is a strong plus.

Velocity and Adaptability: An aggressively entrepreneurial spirit with a track record of moving fast, delivering results quickly, and an insatiable hunger for learning and immediately leveraging new AI technologies and tools.

Customer Obsession: A strong desire to be close to the customer, with demonstrated experience running A/B tests, prototypes, or rapid user experiments..

Strong Computer Science / Data Science fundamentals including data structures, algorithms, performance complexity, data analysis, model training, A/B testing, and MLOps practices.