Applied AI Engineer - Enterprise Solutions

Role overview A customer-facing applied AI engineering role focused on designing and delivering generative AI and machine learning solutions for enterprise clients. The position bridges cutting-edge research with practical business outcomes, helping organizations build specialized AI systems that leverage their proprietary data for measurable impact.

Responsibilities - Partner with enterprise customers to scope use cases, explore data, and develop and deploy Gen AI and ML solutions end to end. - Build applied AI systems using techniques such as retrieval-augmented generation, fine-tuning pipelines, prompt engineering, and agentic workflows. - Design augmented datasets and evaluation workflows that ensure model reliability, transparency, and stakeholder trust. - Manage relationships with customer leadership and stakeholders across project lifecycles to drive successful deployments. - Collaborate with pre-sales and product teams to map customer needs to existing capabilities and surface roadmap gaps. - Standardize recurring solutions into reusable recipes, contribute to internal tooling, and lead enablement workshops for customer teams.

Requirements - Bachelor's degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics, or equivalent experience. - Three or more years of customer-facing experience designing and implementing AI/ML solutions. - Strong proficiency in Python with solid software engineering fundamentals, including modular design, testing, profiling, and packaging. - Hands-on experience with modern Python tooling for type validation, typed data modeling, type-safe systems, API frameworks, and ML orchestration. - Broad expertise across the applied AI stack, spanning classical ML libraries, deep learning frameworks, foundation-model ecosystems, vector and embedding tooling, data processing frameworks, RAG tooling, and LLM orchestration and agent-authoring frameworks. - Experience leading strategic, customer-facing initiatives and collaborating across product, engineering, and business stakeholders.

Nice to have - Strong presentation skills with the ability to communicate clearly to both technical and executive audiences. - Comfort working in a fast-paced environment and balancing priorities across multiple concurrent projects.

Benefits and work setup - Hybrid work model based in San Francisco, CA or New York, NY. - Equity compensation through employee stock options. - Annual travel up to 25% for customer engagements. - Salary range of $175,000 to $300,000 USD, depending on location and experience.