Define and lead the technical vision for Cresta’s next-generation Agentic AI systems, including Agentic Assist and enterprise AI Agents.
Architect scalable, production-grade LLM systems that integrate reasoning, retrieval, planning, tool use, and real-time decision-making into cohesive, intelligent workflows.
Design and evolve multi-agent orchestration frameworks that combine RAG, structured knowledge, domain-adapted models, and automated actions.
Establish best practices for building robust, reliable, and cost-efficient LLM-powered systems in high-scale production environments.
Own evaluation strategy for complex, non-deterministic AI systems, including offline benchmarking, online experimentation, LLM-as-a-judge methodologies, and systematic failure analysis.
Proactively identify and mitigate agent failure modes such as hallucinations, tool misuse, retrieval errors, prompt brittleness, context drift, and multi-step reasoning breakdowns.
Define measurable quality standards (accuracy, faithfulness, task completion, latency, cost efficiency, robustness) and drive continuous system improvement.
Influence cross-team architecture decisions across ML, backend, and product engineering to ensure seamless integration of AI capabilities.
Mentor senior engineers, raise the technical bar, and contribute to long-term AI strategy and roadmap planning.
Translate cutting-edge research advances into practical, high-impact production systems.

Requirements

Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or Ph.D. strongly preferred.
7+ years of experience building and deploying machine learning systems in production, including deep hands-on experience with LLMs at scale.
Demonstrated leadership in architecting complex AI systems, particularly agentic or multi-step LLM workflows.
Deep expertise in transformer-based models, embeddings, retrieval systems, and Retrieval-Augmented Generation (RAG) pipelines.
Experience designing evaluation frameworks for LLM systems beyond single-turn prompts, including robustness testing and production monitoring.
Strong systems thinking: ability to design for scalability, latency constraints, cost efficiency, security, and long-term maintainability.
Extensive experience with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
Proven ability to influence technical direction across teams as a senior individual contributor.
A strong bias toward action — able to prototype rapidly while maintaining production rigor.

Benefits

Comprehensive medical, dental, and vision coverage with plans to fit you and your family
Flexible PTO to take the time you need, when you need it
Paid parental leave for all new parents welcoming a new child
Retirement savings plan to help you plan for the future
Remote work setup budget to help you create a productive home office
Monthly wellness and communication stipend to keep you connected and balanced
In-office meal program and commuter benefits provided for onsite employees

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learning systemsLLM systemstransformer-based modelsembeddingsretrieval systemsRetrieval-Augmented Generation (RAG)evaluation frameworksrobustness testingscalabilitycost efficiency

Soft Skills

leadershipsystems thinkingmentoringinfluencing technical directionprototypingaction-oriented

Certifications

Bachelor’s degree in Computer ScienceMaster’s degreePh.D.