AI Engineer

What You’ll Do

• Architect AI Infrastructure: Design and build backend services, data pipelines, and orchestration workflows for LLMs and agent-based systems.

• Ship Production-Grade Code: Write high-performance, clean, testable code to serve high-throughput AI workflows and data-driven systems.

• Integrate & Scale: Build resilient APIs and pipelines integrating foundational models, vector data stores, and backend microservices across cloud environments.

• Drive Productization: Translate ambiguous enterprise client problems into robust, scalable platform components and reusable AI products.

• Cross-Functional Collaboration: Partner directly with ML engineers, product leads, and frontend developers to rapidly ship cutting-edge AI capabilities.

What We’re Looking For

• Core Backend Mastery: Strong problem-solving and analytical skills with solid fundamentals in modern backend technologies (Python, Go, Java, or Node.js).

• System Architecture: Solid understanding of data structures, REST/gRPC APIs, SQL/NoSQL databases, and distributed systems design.

• AI/ML Technical Exposure: Hands-on experience or direct exposure to LLMs, RAG frameworks (e.g., LangChain, LlamaIndex), model integrations, or AI/ML data pipelines.

• Production Operations: Proven track record of building, deploying, operating, and scaling backend systems in production cloud environments.

• Problem-Solving Mindset: Ability to take ambiguous business and technical requirements and turn them into robust, clean software solutions.