4 months ago
Remote, United StatesSenior
Base Salary
$85k - $120k/yr
Responsibilities
- Design production-ready agentic architectures covering tool use, intent parsing, orchestration, error recovery, and safety guardrails.
- Define consistent multimodal interfaces across UI, API, SDK, and agentic natural-language experiences.
- Design shared LLM platform capabilities including RAG pipelines, prompt libraries, vector search infrastructure, and evaluation frameworks.
- Rapidly prototype AI product hypotheses and validate them with product teams before larger engineering investment.
- Establish observability, documentation, and runbooks so product engineering teams can independently operate the systems.
- Influence AI product strategy, prioritization, trade-offs, and the definition of agent-ready product surfaces.
- Select and govern LLM providers and deployment strategies based on cost, latency, accuracy, and privacy.
- Mentor engineers on LLM integration, agent evaluation, and production deployment practices.
Requirements
- 5+ years of engineering experience, including at least 2 years designing and deploying LLM-powered systems in production.
- Production experience designing agentic systems with tool use, function calling, multi-step reasoning, orchestration, and error recovery.
- Experience designing AI systems for ownership by engineering teams, including observability standards, documentation, and runbooks.
- Hands-on experience with OpenAI, Anthropic, Google Gemini, and at least one open-source model stack.
- Experience building RAG pipelines with vector databases and orchestration frameworks such as LangChain, LlamaIndex, or custom solutions.
- Strong Python engineering skills for production-grade LLM services.
- Ability to influence product direction and communicate architectural trade-offs to engineers and business outcomes to executives.
- Preferred experience in gaming, payments, or e-commerce and familiarity with developer workflows, monetization, or merchant operations.
- Preferred fine-tuning experience using PEFT or LoRA.
- Preferred experience with multi-agent frameworks such as AutoGen or CrewAI.
- Preferred familiarity with LLM evaluation frameworks such as RAGAS or DeepEval.
- Preferred exposure to the EU AI Act, GDPR, or other AI compliance frameworks.
Benefits
- 100% company-paid medical, dental, and vision plans.
- Unlimited Flexible Time Off.
- Personalized career roadmap and professional development through training and educational opportunities.
- Xsolla states that it provides a supportive environment focused on employee and family well-being.
Tech Stack
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