
A global software development company is looking for a talented Senior AI Engineer to join their growing team.
трт На сервисе с: 13.10.26 15:12
A global software development company is looking for a talented Senior AI Engineer to join their growing team.
The company develops a highly scalable technology platform designed to help businesses and professionals optimize complex, multi-step operations. Its proprietary software combines advanced algorithms, intelligent automation, mapping, and real-time decision-making capabilities to make everyday operations more efficient and predictable.
The platform is built entirely on proprietary technology and runs on a highly scalable cloud infrastructure designed for continuous, mission-critical performance. The team is fully remote and consists of experienced professionals who have demonstrated strong technical expertise, problem-solving abilities, and resilience in demanding environments.
About the role
Company are building an AI layer across its platform: an in-app copilot that answers questions and takes actions, analytics assistants over our data warehouse, an MCP server that exposes 100+ platform tools to AI assistants, and multi-agent systems that automate dispatching.
As a Senior AI Engineer, you will design, ship and operate these systems in production, end to end. The AI stack is Python on Google Cloud (Vertex AI, Cloud Run, BigQuery) with several model providers (Gemini, Claude).
As an AI Engineer you will:
Build and own the in-app AI copilot that answers questions and performs actions on routes, orders, drivers and vehicles;
Extend our MCP server (100+ tools) so AI assistants can work with the platform safely;
Design multi-agent systems for automated dispatching, with agent routing and human approval for risky actions;
Build AI analytics: natural-language questions and insight reports over our BigQuery data;
Own the AI platform layer: prompt and model versioning, model routing, caching, guardrails, tracing, cost and latency;
Write design docs and ADRs; work with the PO, backend (PHP/Python) and frontend teams; share AI practices across the team;
Requirements:
5+ years of commercial software engineering, Python as the primary language (async, typing, testing; FastAPI or similar);
2+ years building and shipping LLM-powered products to production for real users;
MCP servers: design and build MCP servers and tools on top of existing REST APIs (auth, multi-tenancy, rate limits, error handling);
AI chats: production conversational assistants with multi-turn context, streaming, tool calling and structured outputs;
Agents: tool-using agents with planning, state, retries, termination conditions and human-in-the-loop for risky actions;
Agent systems: multi-agent orchestration (supervisor/worker, handoffs, shared state) with LangGraph, Google ADK, OpenAI Agents SDK or custom code;
Agent routing: intent classification and routing between agents, tools and models by task, cost and latency, with fallbacks;
RAG: chunking, embeddings, vector and hybrid search, reranking, grounded answers with citations;
System prompting and context engineering: versioned system prompts, tool descriptions, few-shot examples, context window management, prompt-injection defense;
Modern AI architecture: model abstraction across providers (Gemini, Claude, OpenAI), caching, guardrails, tracing and observability, cost and latency control;
Cloud and delivery: GCP or AWS, Docker, CI/CD (GitHub Actions), monitoring;
Security for AI actions: tenant isolation, least-privilege tools, audit logs;
AI-assisted development as a daily habit (Claude Code, Cursor, Copilot);
English B2+ (written and spoken); clear design docs and ADRs;
Nice to have:
Production evals: golden datasets, CI regression gates, LLM-as-judge, A/B tests of prompts and models;
Google Cloud: Vertex AI (Gemini, Agent Engine, prompt management, context caching), Cloud Run, BigQuery, Pub/Sub;
Text-to-SQL and analytics agents over BigQuery-scale data;
Workflow engines: Google Workflows, Temporal, or event-driven pipelines (Pub/Sub, Kafka);
Long-term (semantic) memory for agents, scoped per tenant;
Frontend for AI UX: TypeScript with Vue or React/Next.js (streaming chat UIs);
Kubernetes (GKE), Helm, Terraform;
Ability to read PHP/Laravel code (our core platform APIs);
Fine-tuning or serving open-weights models (Gemma, Llama, Qwen; vLLM);
Optimization tools: OR-Tools, VRP heuristics;
Published MCP servers, connectors or open-source work in AI tooling.
Benefits:
Semi-flexible working hours;
Completely remote work;
Interesting projects to work on;
Exposure to a variety of industries and technologies.
Мы в поиске Senior AI инженера в международную компанию.
О вакансии
Компания создает слой искусственного интеллекта на своей платформе: встроенный в приложение помощник, который отвечает на вопросы и выполняет действия, аналитические помощники на базе нашего хранилища данных, сервер MCP, предоставляющий более 100 платформенных инструментов для помощников с искусственным интеллектом, и мультиагентные системы, автоматизирующие диспетчеризацию.
В качестве старшего инженера по искусственному интеллекту вы будете проектировать, внедрять и эксплуатировать эти системы в производственной среде. Стек — Python на Google Cloud (Vertex AI, Cloud Run, BigQuery) с несколькими поставщиками моделей (Gemini, Claude).
HireSeeker собирает вакансии со всех площадок и присылает только релевантные. Бесплатно.