LLM Solutions Architect

Xsolla

3d • Remote

About The Position

Xsolla is seeking an LLM Solutions Architect to join their Monetization Products team. This role acts as a bridge between product strategy and engineering architecture, focusing on designing and prototyping LLM-powered systems. The architect will be responsible for defining an 'Agents-first' approach, integrating natural language, agentic control, and multi-modal interfaces with existing Xsolla products. The designs must be scalable, maintainable by engineering teams, and include clear documentation, observability, and runbooks for long-term ownership. This is a hands-on role focused on building and system design, not pure research or product management.

Requirements

• 5+ years of engineering experience.
• At least 2 years designing and deploying LLM-powered systems in production.
• Proven track record designing agentic systems: tool-use, function calling, multi-step reasoning, orchestration, and error recovery at production scale.
• Experience designing AI systems for engineering team ownership, including observability standards, handoff documentation, and runbooks.
• Hands-on experience with major LLM APIs (OpenAI, Anthropic, Google Gemini) and at least one open-source model stack.
• Experience building RAG pipelines with vector databases and orchestration frameworks (LangChain, LlamaIndex, or custom).
• Strong Python engineering skills for production-grade LLM services.
• Demonstrated ability to influence product direction.
• Clear communication skills, able to explain architectural trade-offs to engineers and business outcomes to executives.

Nice To Haves

• Background in gaming, payments, or e-commerce.
• Fine-tuning experience (PEFT/LoRA) for domain-specific model adaptation.
• Experience with multi-agent orchestration frameworks (AutoGen, CrewAI, or custom).
• Familiarity with LLM evaluation frameworks (RAGAS, DeepEval, or custom harnesses).
• Exposure to EU AI Act, GDPR, or other AI compliance frameworks.

Responsibilities

• Design end-to-end agentic architectures, including tool-use schemas, intent parsing, multi-step orchestration, and safety guardrails, engineered for long-term ownership by product engineering teams.
• Define the multi-modal interface strategy across the product portfolio, ensuring consistent exposure via UI, API, SDK, and agentic natural language.
• Design the horizontal LLM platform layer, including shared RAG pipelines, prompt libraries, vector search infrastructure, and evaluation frameworks.
• Prototype rapidly to validate AI product hypotheses before full engineering investment.
• Ensure all architected systems include observability, documentation, and engineering runbooks for product squad ownership.
• Shape product strategy alongside Product leadership, influencing AI capability prioritization and trade-offs.
• Select and govern LLM providers and deployment strategies based on cost, latency, accuracy, and privacy requirements.
• Drive alignment across Engineering, Product, and Design on 'agent-ready' definitions for product surfaces.
• Mentor engineers on LLM integration patterns, agent evaluation, and production deployment practices.

Benefits

• 100% company-paid medical, dental, and vision plans
• Unlimited Flexible Time Off
• Personalized career roadmap
• Investment in professional development through training and educational opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed