Role & seniority: Senior AI/ML Engineer (focus on internal AI agent ecosystem and data platform)

Stack/tools: Python; FastAPI; RESTful APIs; web crawlers (Scrapy, BeautifulSoup, Selenium); data processing (pandas, numpy); LLM-based apps; agentic RAG architectures; potential exposure to LangChain, LangGraph, CrewAI, AutoGen; vector databases (e.g., Pinecone, Weaviate, Milvus, Chroma)

Top 3 responsibilities

Develop and maintain the internal AI agent ecosystem and agent-based data platform, including autonomous agents for data collection, review, and structuring from external sources
Build robust automation workflows and data pipelines processing game metrics (revenue, DAU, player activity) to enable data-driven decisions across teams
Design/implement APIs and services with FastAPI to support agent interactions, data ingestion, and internal tool integrations

Must-have skills

Proven track record building LLM-based applications with prompt optimization, context engineering to reduce errors/hallucinations
Strong Python proficiency: FastAPI or similar REST APIs; web crawling/scraping (Scrapy, BeautifulSoup, Selenium); data processing (pandas, numpy)
Experience with agentic RAG architectures and autonomous information retrieval/use
Excellent communication and collaboration across cross-functional/global teams
Passion for mobile games

Nice-to-haves

Experience with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen)

Full Description

WHAT WE EXPECT

You will

Develop and maintain our internal AI agent ecosystem and agent-based data platform, including autonomous agents that collect, review, and structure data from external sources into our databases.
Build robust automation workflows and data pipelines that process game performance metrics (revenue, DAU, player activity) and enable data-driven decision making across teams.
Design and implement APIs and services using FastAPI to support agent interactions, data ingestion, and internal tool integrations.
Develop data collection systems and web crawlers to gather and structure information from external partners, APIs, and web sources with proper error handling and data validation.
Collaborate with engineering and operations teams to identify automation opportunities and expand the capabilities of our agentic systems.

You must have

Proven experience building LLM-based applications and dealing with practical challenges like prompt optimization and context engineering to optimize LLM performance, fix hallucinations, and reduce errors.
Strong Python proficiency with experience in (a) building RESTful APIs using FastAPI or similar frameworks; (b) developing web crawlers and data scrapers such as Scrapy, BeautifulSoup, Selenium, or custom solutions; and (c) data processing and transformation using pandas, numpy, or similar libraries.
Experience with agentic RAG architectures, building RAG systems where agents autonomously determine what information to retrieve and how to use it.
Strong communication and collaboration skills within cross-functional and globally distributed teams.
Passion for mobile games!

You might have

Experience with agent orchestration frameworks such as LangChain, LangGraph, CrewAI, and AutoGen.
Background in data pipeline orchestration tools such as Airflow, Prefect, and Dagster.
Experience with async Python programming and high-concurrency applications
Familiarity with vector databases such as Pinecone, Weaviate, Milvus, and Chroma for RAG implementations.
Experience with API rate limiting, retry strategies, and building resilient distributed systems.
Previous work on multi-agent systems, coordinating multiple specialized agents.
Experience working with collaboration and automation tools like Notion and n8n.
Kubernetes deployment and debugging experience - hands-on work deploying services, reading logs, and troubleshooting issues.
Experience working with teams across different locations, cultures, and time zones.

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Python Automation Engineer