AI Engineer
Build full-stack AI prototypes and agentic systems to pressure-test venture ideas. Requires 3+ years building production AI applications with strong frontend/backend fluency and frontier coding agent expertise.
AI Agent Engineer
Builds complex AI agent pipelines using LLMs, develops ML models with fine-tuning pipelines, and deploys AI infrastructure on cloud platforms. Requires 5+ years experience, expertise in AI/ML systems, and bachelor's degree or higher.
150k – 230kSan Jose, CAML EngineeringOnsite5+ YOE
About the role
Key Responsibilities
AI Agent Building (60%)
- Develop complex multi-step agentic pipelines around open- and closed-source LLMs.
- Build tools enabling AIs to interact with critical enterprise software platforms.
- Ensure AI designs align with business objectives and industry best practices.
ML development and fine-tuning (30%)
- Create data generation and processing pipelines to train and fine-tune custom ML models.
- Implement and manage training and evaluation pipelines for LLMs.
Deployment and AI Systems Infrastructure (10%)
- Manage AI infrastructure across platforms such as AWS, Azure, or GCP.
- Deploy inference endpoints and serve AI and LLM technologies as part of our core product infrastructure.
Required Qualifications
- Earned a Bachelor’s degree, Master's degree or Ph.D. in Computer Science, Engineering, or a related field.
- 5+ years of experience in software engineering, platform engineering, or related roles.
- Proven expertise in AI model building and agent development.
- Strong background in ML and LLM-driven systems development.
- Experience with compound AI systems, vector databases, and tool-calling AIs.
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
Preferred Qualifications
- Experience building & deploying production-grade, large-scale AI applications.
- Familiarity with AI deployment, evaluation, and monitoring practices.
- Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.
Skills
LLMsAI AgentsMachine LearningVector DatabasesTool CallingAWSAzureGCPFine-TuningData Pipelines
Similar roles
ML Engineering jobsMachine Learning Engineer
Build and deploy ML models for entity resolution and knowledge graph expansion on large-scale China-related data. Requires 4+ years clustering ML experience and end-to-end production ML with Python/SQL.
Research Engineer, Post-Training
Research Engineers design and run post-training workflows, build evaluation infrastructure, and turn frontier AI techniques into reliable production systems for enterprise customers. Requires experience with fine-tuning, RLHF, reward modeling, and strong experimentation skills.
Research Engineer, Agents
Research Engineers build and productionize agentic AI systems, designing compound architectures, evaluation frameworks, and reliable execution for enterprise workflows. Requires strong Python skills, systems reasoning, and experience building agents with tools, retrieval, planning, and memory.