Senior Software Engineer, AI Agents; Autonomous Systems — Gaia

Gaia is building the next generation of  experiences using AI. This role focuses on designing and shipping agentic, autonomous software systems that can plan, act, evaluate outcomes, and continuously improve—driving real product impact, not demos. You’ll build production‑grade AI agents that meaningfully enhance customer experience, operational efficiency, content intelligence, personalization, and discovery across  This is a builder role: you’ll move fast, iterate relentlessly, and own outcomes end‑to‑end—from problem framing and system design to deployment, observability, and continuous optimization.

At Gaia, soft skills are key to success. We seek candidates with strong interpersonal abilities – effective communication, teamwork, prioritization, and problem solving – who can adapt to change, manage conflicts with empathy, and collaborate well with diverse teams. While technical skills matter, we highly value those who build positive relationships, contribute to a supportive culture, and approach challenges with a solution‑oriented mindset.

If this sounds like you, you’ll thrive in our dynamic environment. Must be able to work on campus in Louisville, CO. US citizenship or an existing work visa is required Gaia subscribers strongly preferred Non‑smoker

• Architect and implement agentic AI systems that autonomously execute multi‑step workflows (planning, tool use, memory, evaluation, refinement).
• Build and own production services in Python that orchestrate LLM‑based reasoning, retrieval, tool calling, and safe action execution.
• Design autonomy loops: task decomposition, reflection/self‑critique, reward signals, evaluation harnesses, and guardrails.
• Develop robust RAG pipelines for Gaia’s content ecosystem (semantic search, chunking, embeddings, reranking, citations, freshness).
• Create frameworks for agent reliability: testing, simulation, regression suites, red‑team‑ing, and continuous evaluation.
• Implement observability for LLM systems: tracing, cost/latency monitoring, failure taxonomy, quality metrics, and incident response.
• Partner with product, design, and content teams to translate Gaia’s mission and user needs into autonomous capabilities.
• Optimize for performance and cost: caching, batching, model routing, quantization (where relevant), and prompt/system improvements.
• Ship continuously: build, measure, learn—tight loops, pragmatic decisions, and visible progress.

• Expert‑level Python and experience building production services (APIs, workers, pipelines, orchestration).
• Deep knowledge of LLMs and agentic systems, including strengths/limits, failure modes, and practical patterns for reliability.
• Proven track record of execution: you ship, you iterate, you improve outcomes based on real signals.
• Strong “builder + owner” mindset: you take ambiguous problems, create clarity, and deliver results.
• Entrepreneurial mindset: bias toward action, comfort with uncertainty, high accountability, and strong product instincts.
• Solid foundation in mathematics, statistics, and data reasoning (you can quantify uncertainty, validate improvements, and avoid hand‑wavy conclusions).
• Strong data fluency: instrumentation, metrics design, experiment analysis, and operational decision‑making using data.

• Hands‑on experience building agentic workflows using modern frameworks (e.g., Lang Graph/Lang Chain, Llama Index, Semantic Kernel, or equivalent custom stacks).
• Experience with tool‑using agents: function calling, structured outputs, constrained decoding, and robust schema validation.
• Experience with evaluation techniques for LLM systems (golden sets, model‑graded evals, pairwise ranking, offline/online correlation).
• Experience with retrieval systems: vector databases, hybrid search, reranking, query rewriting, and content freshness strategies.
• Knowledge of prompt/system design for production (instruction hierarchies, routing, safety constraints, and jailbreak resistance).
• Experience with distributed systems and async execution patterns (queues, orchestration, retries, idempotency, back pressure).
• Experience deploying and scaling LLM‑enabled services in cloud environments…