Senior LLM Systems Engineer

• •**LLM Accuracy:** improve prompts, model selection, tool usage, structured outputs, retrieval, and evaluation coverage so the system gets more decisions right over time.
• •**System Performance:** reduce latency, token usage, and cost while preserving decision quality and operational reliability.
• •**Resilience:** design validation, retries, fallbacks, uncertainty handling, and human review paths for ambiguous, adversarial, incomplete, or conflicting inputs.
• •**Evaluation and Monitoring:** build datasets, regression tests, dashboards, traces, and review loops that make model quality visible and prevent repeated failures.
• •**Agent and Tooling Architecture:** Improve agent orchestration and tool use across internal services, APIs, search workflows, databases, and external data sources.
• •**Production Operations:** help debug live issues, investigate regressions, improve runbooks, and reduce repeated operator friction.

• •Pay packages include competitive salaries & meaningful long term equity participation.
• •Salaries for this role range from $100-200k (USD).
• •Will pay in stablecoins or fiat.
• •Philosophies for a culture that show we care: Take vacation when you need it, family care, training and development (just to name a few).
• •100% remote, which means we encourage you to create the work environment that you thrive in.
• •At least two team wide offsites a year.

#### Required

• •3+ years of professional software engineering experience in Python, TypeScript, or similar production languages.
• •Hands-on experience building production systems that use LLMs, agents, retrieval, structured outputs, or model-powered workflows.
• •Experience designing evaluations, test datasets, regression checks, quality metrics, or manual review loops for AI systems.
• •Strong debugging ability across APIs, databases, queues, logs, model outputs, and external data sources.
• •Practical understanding of prompt engineering, tool calling, structured output validation, retrieval, and common LLM failure modes.
• •Ability to reason carefully about correctness in uncertain or adversarial environments.
• •High agency, strong ownership, and clear written communication.

#### Nice to Have

• •Experience with oracle systems, prediction markets, DeFi protocols, or other crypto infrastructure.
• •Experience with UMA, optimistic oracle mechanisms, Polymarket, or similar systems.
• •Experience building agentic systems that use tools, search, browser automation, APIs, or database queries.
• •Experience with LLM tracing, model monitoring, evaluation frameworks, or AI observability tools.
• •Experience optimizing model cost and latency at scale.
• •Experience with Postgres, data pipelines, queue-based systems, background jobs, or event-driven architectures.
• •Familiarity with blockchain operational constraints, especially RPC limits, indexing, event logs, finality, and chain-specific behavior.
• •Experience with GCP, Cloud Run, GitHub Actions, Terraform, or similar infrastructure.