Senior AI Engineer

About the Role

As a Senior AI Engineer, you will play a key role in designing and building intelligent systems at the core of our platform. In this early-stage startup environment, you will work hands-on across the stack, focusing on developing AI-powered features, integrating large language models (LLMs), and shaping the architecture of scalable, production-ready AI systems.
You will contribute directly to building data-driven and AI-first capabilities, while influencing technical direction and helping define how AI is embedded across the product.

What You'll Do

• Design, build, and deploy AI-powered backend services and APIs using Python (Django or similar frameworks)
• Develop and integrate LLM-based solutions (e.g., RAG pipelines, agents, prompt workflows) into production systems
• Build and maintain data pipelines (ETL) to support model training, inference, and analytics
• Own the end-to-end lifecycle of AI features — from experimentation and prototyping to deployment and monitoring
• Architect scalable systems for multi-tenant AI SaaS platforms, ensuring performance, security, and reliability
• Collaborate with product and business stakeholders to translate requirements into AI-driven solutions
• Evaluate, select, and optimize models (LLMs/SLMs), including fine-tuning, prompt engineering, and benchmarking
• Stay up to date with the latest advancements in AI/ML, LLM tooling, and agent frameworks, and apply them to real-world problems
• Contribute to the technical roadmap, driving adoption of AI capabilities across the platform

What You'll Need

• Strong background in AI/ML systems and software engineering, including designing scalable, production-grade architectures
• Hands-on experience with: Python and backend development
• LLM frameworks (e.g., LangChain or similar)
• Messaging/async systems (Celery, RabbitMQ, etc.)
• Experience building and deploying AI-powered applications, including:
• RAG pipelines
• AI agents
• Experience working with cloud platforms (Azure preferred; AWS/GCP is a plus)
• Understanding of data systems, including ETL pipelines and data-driven product development
• Familiarity with ML frameworks such as TensorFlow or PyTorch is a plus
• Ability to navigate ambiguity and solve complex problems in AI-driven systems
• Strong communication skills, with the ability to explain AI concepts to both technical and non-technical stakeholders