Job Details

About the Role

This is a rare opportunity to work hands-on with LLMs, knowledge graphs, and retrieval systems (RAG) in production. You'll architect core infrastructure for AI systems that push the boundaries of reasoning, scalability, and usability — all while working closely with a world-class technical team in San Francisco (on-site).

This is a role for an engineer who thrives at the intersection of AI research and real-world systems, with the autonomy to innovate, experiment, and ship fast.

Key Responsibilities

• Architect and advance the backbone of an AI reasoning platform using LLMs and retrieval-based knowledge systems.
• Build and optimize RAG pipelines, embeddings, and eval frameworks to improve AI response quality.
• Collaborate across AI, backend, and infrastructure teams to ship reliable, production-ready systems.
• Define metrics, testing, and monitoring for model performance and accuracy.
• Push the boundaries of AI–human interaction through research-driven prototyping.

Required Experience

• 4–5+ years of professional software engineering experience (Python, backend, or AI systems).
• Hands-on experience building or deploying LLMs / applied AI systems in production.
• Proven work with retrieval systems (RAG, vector search, knowledge graphs, embeddings).
• Strong understanding of backend architecture and cloud infrastructure (AWS/GCP).
• Experience in 0→1 product development at a high-growth startup or elite tech company.
• Willingness to work on-site in San Francisco with the core AI team.

Nice-to-Have

• Experience fine-tuning or benchmarking LLMs.
• Prior work in graph data systems, symbolic reasoning, or AI-driven product design.
• Open-source or public demos showcasing applied AI experimentation.

Why Candidates Should Join

• Category-defining mission: Build next-generation AI systems that model human intelligence.
• High-impact engineering: Shape core architecture and product direction from the ground up.
• Elite team & backers: Backed by Sequoia, Founders Fund, and top-tier AI operators.
• Cutting-edge stack: Work with LLMs, RAG, knowledge graphs, and multi-agent frameworks.
• On-site collaboration: Join an ambitious, highly technical team in San Francisco.

Skills & Mindset

• Relentless curiosity and deep technical intuition.
• Systems thinker who thrives in ambiguity and experimentation.
• Pragmatic builder who ships fast and learns faster.
• Low-ego collaborator driven by craft, quality, and impact.

Logistics & Compensation

• Employment: Full-time, On-site (San Francisco, CA)
• Base Salary: $200K – $350K USD
• Equity: Competitive package
• Visa: Sponsorship available (H1B, O1) + relocation support

Confidentiality Statement

Confidentiality: At Quix Recruitment, we prioritise confidentiality throughout the recruitment process. We understand the sensitivity of exploring new career opportunities while currently employed. Rest assured that when you apply through Quix Recruitment, your application is kept completely confidential from both your current employer and the hiring company. If we determine that you might be a good fit for the position, we will arrange a confidential call with you to discuss the opportunity in more depth. Only after obtaining your permission will we share your CV with the hiring company.

Disclaimer

Please note that all personal information collected during the application process will be used for recruitment-related purposes only. We are committed to protecting your privacy and will not disclose your information to any third parties without your consent.