Member of Technical Staff, Forward Deployed AI Engineer

4 months ago

San Mateo, CA, USASenior

Responsibilities

Work directly with strategic enterprise customers to identify high-value AI workflows and deliver production deployments.
Build full-stack AI applications, agentic workflows, integrations, internal tools, and customer-facing systems.
Run rapid proof-of-concept cycles and iterate on customer requirements and technical constraints.
Collect, structure, and operationalize customer data to improve model and product performance.
Define deployment success metrics and build LLM-as-judge workflows, evaluation harnesses, and feedback loops.
Tune and customize models, prompts, workflows, and system architecture for customer-specific goals.
Build agentic workflows involving classification, routing, context compaction, search, coding agents, and voice applications.
Convert customer-specific solutions into repeatable product patterns, evaluation frameworks, playbooks, and platform capabilities.
Collaborate with platform, serving, post-training, product engineering, and go-to-market teams.
Travel occasionally for strategic deployments, workshops, and executive technical sessions.

Bachelor’s, master’s, or doctoral degree in computer science, machine learning, or a related field, or equivalent experience.
Strong Python and modern full-stack development skills, including APIs and backend systems, with TypeScript or JavaScript preferred.
Experience building, deploying, or integrating AI or LLM products used by real users or customers.
Familiarity with LLM evaluation, LLM-as-judge workflows, data pipelines, model tuning, prompt optimization, or agentic workflows.
Customer-facing experience with enterprise, strategic, or high-value accounts.
Experience deploying software or AI systems in enterprise environments with security, privacy, reliability, compliance, or integration constraints.
Strong communication and discovery skills for translating ambiguous customer needs into technical solutions.
Ability to work across engineering, product, sales, and customer success with limited process or supervision.
Preferred experience includes RAG, search, voice AI, coding agents, agentic workflows, Fortune 500 deployments, technical pre-sales or post-sales, implementation, customer expansion, LLM serving, latency optimization, model evaluation, production ML systems, data engineering, synthetic data, and customer-specific benchmarks.

In-office role at an early-stage company with a fast-moving startup environment.
Occasional customer travel for strategic deployments, workshops, and executive technical sessions.
High-leverage opportunity to work directly with enterprise customers and own end-to-end deployment problems.

51-200 employees