AI-инженер (LLM, агенты, AI product) вакансии - в офисе

Location: Montreal Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.   For more information, visit xsolla.com. Responsibilities: Design and develop full-stack applications that power GenAI applications and platforms Develop and maintain frontend applications using Next.js with API routes. Design and implement visually appealing and responsive user interfaces using Tailwind CSS / Shadcn or other CSS libraries. Write clean, efficient, and scalable code in Python and TypeScript . Work with various libraries or frameworks based on project requirements. Be up-to-date with latest happenings in AI and Associated AI tools, technologies and frameworks (e.g. MCP, Agentic systems) Build APIs and infrastructure to support LLM-based features, tools, and agent workflows. Collaborate with frontend, ML, and product teams to create seamless AI experiences. Optimize backend systems for performance, scalability, and reliability. Work with vector databases, data pipelines, and AI model endpoints (OpenAI, Anthropic, Hugging Face, etc.) Maintain clean, secure, and production-grade code Qualifications & Skills: 1–3 years of experience in full-stack development. Proficient in Python and Typescript. Strong experience with REST APIs, microservices, and scalable cloud infrastructure. Experience building or supporting GenAI applications and/or LLM-powered products. Comfortable working with and building Agentic systems (e.g. building custom Lovable or Claude Code for custom applications) Exposure to cloud services (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) Excellent problem-solving, communication, and collaboration skills Nice to Have: Experience building and scaling AI-powered SaaS products Contributions to open-source GenAI projects Understanding of context engineering and agent orchestration frameworks Benefits:We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.    Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Full Stack AI Engineer, we will conduct a background check that may include the following. Criminal history check. Employment verification. Education verification.   Relevance to job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements Handling sensitive financial information/ managing budgets /accessing funds

Location: London Workplace: OnSite About Clarity We’re pioneering Agentic AI — systems that don’t just respond, but reason, act, and adapt autonomously in complex workflows. This is about crafting AI Agent Experiences — designing agents that collaborate seamlessly with humans, learn from context, and make every customer interaction faster, smarter, and more empathetic. You’ll own the technical vision and turn requirements into a live, reliable product used by brands like Grubhub, Booking.com http://Booking.com, Dropbox, Uber, Careem, and Fubo. You’ll collaborate directly with engineers, other tech leads, directors, and the CTO to evolve ambitious prototypes into a rock‑solid, scalable platform What you’ll actually do 50% Build — design & ship - Agentic AI for CX: Real‑time assistants that listen to calls/chats, retrieve from customer KBs, and draft responses with human‑in‑the‑loop controls. - Structured extraction: Schema‑driven pipelines over unstructured text (and other modalities) using retrieval, tool‑use, and robust LLM prompting. - Hybrid anomaly detection: Blend classical time‑series methods (e.g., decomposition, change‑point, forecasting) with LLM‑aware, contextful detectors for seasonality, spikes, step‑changes, and drift. - Novelty discovery: Embedding‑based clustering and drift, topic surfacing, LLM summarization of emerging themes with deduplication and evidence links. - Alerting & scoring: Severity/impact ranking, de‑noising, suppression/cool‑downs, routing, and feedback loops. 25% Architect & scale - Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. - Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. - Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost tuning. - Participate in on‑call for your area and drive root‑cause analysis with crisp follow‑ups. 15% Collaborate - Pair with back‑end & front‑end to wire extractors/detectors and agents into ticketing, voice, and analytics stacks (APIs, webhooks, real‑time streams). - Partner with PMs/CX to evolve taxonomies, schemas, and guardrails; translate business problems into shipped ML features. 10% Align & showcase - Gather requirements from CX and product leads, demo new capabilities to execs & customers, and document impact with precision/recall, alert quality, latency, and cost metrics. What makes you a great fit - Startup hacker mindset: You self‑start from zero, respect no silos, and carry work from prototype to production. 🛠️ - AI‑native dev tools are your daily drivers: Cursor, v0, Claude Code (or similar). - 7–10 years building production ML/back‑end systems; 2+ years leading while coding. - Expert Python; strong back‑end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). - Agents & RAG: Fluency with at least one agent framework (ADK preferred). Proven track record shipping AI agents and building RAG pipelines. - LLM + DS depth: Prompting/tooling, retrieval design, LLM evals; hands‑on with time‑series analysis (forecasting, change‑point, drift). - Cloud & ops: Basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost control. - Communication: You explain results clearly, align stakeholders, and write crisp docs. Bonus points - DevOps wizardry; GPU/accelerator experience. - Multimodal pipelines (text + voice + screenshots). - Prior experience in contact center/CX analytics or novelty/anomaly systems. - Founder or founding engineer experience