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Lead Backend Engineer (AI/ML)
Lead Backend Engineer (AI/ML)
As a Lead Backend Engineer (AI/ML), you will design and develop scalable, secure, and high-performance backend systems using Python and cloud-native patterns, with a strong focus on AI-powered solutions. You will be responsible for architecting and implementing features like RAG pipelines, LLM integrations, and intelligent agent systems on Google Cloud Platform, while also leading and mentoring other engineers.
About the role
About the Role
As a Lead Backend Engineer specializing in AI/ML, you will be instrumental in designing and developing scalable, secure, and high-performance backend systems. This role emphasizes modern cloud-native patterns and the application of spec-driven development practices to ensure clarity, quality, and predictable delivery. You will also coordinate teams of coding agents and collaborate extensively with product, UX, and other disciplines to translate backlog requirements into detailed, implementable specifications.
Key Responsibilities
- Lead the design and development of scalable, secure, and high-performance backend systems using Python and modern cloud-native patterns.
- Apply spec-driven development practices to ensure clarity, quality, and predictable delivery.
- Organize, distribute, and translate backlog requirements from Product, UX, and other disciplines into detailed spec-driven requirements for Agents to implement.
- Coordinate teams of coding agents to deliver engineering requirements.
- Design and implement RESTful APIs to support frontend, mobile, and third-party integrations.
- Architect and deliver AI-powered backend solutions, including: Vector stores and Retrieval-Augmented Generation (RAG) pipelines, integration with LLMs (e.g., Gemini, Claude, GPT-4/5), and use of AI coding agents and developer copilots to improve delivery velocity.
- Develop and maintain systems using Google Cloud Platform (GCP), with hands-on experience in Vertex AI and Google Gen AI APIs.
- Leverage Agent Development Kits (ADKs) (e.g., Google ADK) to design and implement intelligent agent-based systems.
- Ensure systems are observable, reliable, and debuggable in production environments.
- Collaborate with engineers to design well-architected, maintainable solutions aligned with business goals.
- Mentor and guide engineers, fostering technical excellence and continuous learning.
- Partner with Project Managers and cross-functional teams to manage delivery risks and timelines.
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders, including clients.