In this role, you will act as the primary architect of the "nervous system" that bridges the gap between sophisticated AI models and real-world business logic. You will design and maintain the critical infrastructure that enables intelligent, autonomous features to function reliably at scale, moving beyond simple API wrappers to build deeply integrated AI systems. You will take ownership of the entire data flow, where you will develop high-performance RAG (Retrieval-Augmented Generation) pipelines and complex agentic workflows that provide users with accurate, context-aware responses.
Your Impact
Champion system stability by implementing rigorous evaluation and monitoring frameworks, ensuring that as our AI capabilities grow, our production environment remains fast, cost-effective, and secure.
Ultimately, you will be the technical force that transforms cutting-edge AI research into stable, scalable products that define the future of our platform.
Your Impact
Champion system stability by implementing rigorous evaluation and monitoring frameworks, ensuring that as our AI capabilities grow, our production environment remains fast, cost-effective, and secure.
Ultimately, you will be the technical force that transforms cutting-edge AI research into stable, scalable products that define the future of our platform.
Requirements:
Your Experience:
Keeps up with the latest research and stays on top of the fast-moving AI space, with a real passion for whats happening in Generative AI.
Regularly tries out different AI tools and sees how theyre useful in everyday work and life.
Strong understanding of advanced prompting techniques like Chain-of-Thought, ReAct, and few-shot prompting.
Experience working on model quantization or finding ways to optimize inference costs and token usage at scale.
Hands-on experience with Python (FastAPI, Django, or Flask) or Go, with a solid grasp of async programming and microservices.
Experience turning a vague product idea (e.g., "let's add a smart assistant") into clear, concrete technical requirements.
Nice to have:
Hands-on experience using frameworks like LangChain to build more complex LLM flows and agents.
Experience working with vector databases.
Comfortable building and using RESTful and GraphQL APIs, especially when dealing with low-latency streaming (WebSockets, Server-Sent Events).
Enjoys digging into non-deterministic systems – when an LLM fails, comfortable figuring out whether its the prompt, the retrieval, or the data.
Familiar with AI-specific security risks, like prompt injection and data leakage.
Your Experience:
Keeps up with the latest research and stays on top of the fast-moving AI space, with a real passion for whats happening in Generative AI.
Regularly tries out different AI tools and sees how theyre useful in everyday work and life.
Strong understanding of advanced prompting techniques like Chain-of-Thought, ReAct, and few-shot prompting.
Experience working on model quantization or finding ways to optimize inference costs and token usage at scale.
Hands-on experience with Python (FastAPI, Django, or Flask) or Go, with a solid grasp of async programming and microservices.
Experience turning a vague product idea (e.g., "let's add a smart assistant") into clear, concrete technical requirements.
Nice to have:
Hands-on experience using frameworks like LangChain to build more complex LLM flows and agents.
Experience working with vector databases.
Comfortable building and using RESTful and GraphQL APIs, especially when dealing with low-latency streaming (WebSockets, Server-Sent Events).
Enjoys digging into non-deterministic systems – when an LLM fails, comfortable figuring out whether its the prompt, the retrieval, or the data.
Familiar with AI-specific security risks, like prompt injection and data leakage.
This position is open to all candidates.
