Applied AI Architect

This is a fully remote position, open to applicants in Arizona.

📋 Description

• Take ownership of the complete AI/ML technical strategy for client accounts, encompassing everything from initial discovery to production deployment and subsequent consumption growth.

• Facilitate intricate architectural discussions and design scalable, production-ready AI/ML solutions that incorporate RAG, tool utilization, multi-agent orchestration, guardrails, AI evaluation, and observability systems.

• Act as a reliable technical advisor to customer architects, engineering leads, and Directors.

• Propel technical victories in competitive scenarios through bespoke solutions that highlight Databricks' unique advantages.

• Cultivate and establish an emerging technical specialization, becoming a key resource for the Field Engineering team.

• Coordinate with DSAs, SAs, and Partners to deliver holistic solutions tailored to complex customer requirements.

• Shape product direction by providing structured feedback on customer needs and identifying competitive gaps.

⛳️ Requirements

• Over 6 years of experience in solutions architecture, technical pre-sales, or a senior hands-on technical position.

• Proficient in ML Engineering, including cloud infrastructure on AWS, Azure, or GCP for supporting production ML applications and monitoring drift.

• Experienced in AI Engineering, encompassing LLMs, agentic systems, vector databases, fine-tuning, AI guardrails, and frameworks like LangChain, Hugging Face, or OpenAI APIs.

• Strong coding skills in Python and SQL, with experience in live coding, debugging, and solution building.

• Extensive knowledge of distributed data systems architecture, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.

• Proficient with the Databricks Platform or capable of achieving proficiency quickly, with an evolving technical specialization.

• Ability to lead architectural discussions with senior technical stakeholders, including whiteboarding, design reviews, and analyzing trade-offs.

• Experience with production deployments on AWS, Azure, or GCP, considering infrastructure, security, and governance aspects.

• Proven track record of driving platform adoption and consumption growth within client accounts.

• Excellent communication skills for conveying complex architectures into business value for both technical and executive audiences.

• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.

• Willingness to travel up to 30% as necessary.

🏝️ Benefits

• Eligibility for an annual performance bonus.

• Equity eligibility.

• Comprehensive benefits and perks, with specific regional details provided through Databricks benefits information.