Fonzi AI, a cutting-edge AI recruiting platform connecting top engineers with pre-vetted startups, is seeking exceptional Senior Product Engineer to build and scale AI-powered products. This is a premier opportunity for a talented engineer with deep expertise in Large Language Models, agentic systems, and end-to-end product development. As Senior Product Engineer, you’ll architect production AI systems handling real users, design retrieval and context engineering strategies, implement agent frameworks, build comprehensive eval pipelines, work with frontier LLM technologies, collaborate with high-growth startups, solve ambiguous problems in startup environments, and drive innovation in AI product development.
About Fonzi AI — AI Recruiting Innovation Leader
Mission: Connect exceptional engineers with pre-vetted early-stage startups
Network: 100+ early-stage companies backed by A16z, Sequoia Capital, YCombinator, General Catalyst
Focus: AI and LLM-driven product engineering for high-growth startups
Locations: Offices in New York City and San Francisco
Culture: Innovation, ambiguity tolerance, startup mindset, cutting-edge AI focus
Senior Product Engineer Role — AI Systems & LLM Focus
Focus Area: AI-powered product development and LLM systems
Scope: End-to-end product development, not prototypes but production systems
Tech Stack: LLMs, agentic systems, retrieval, memory, context engineering, eval pipelines
Mission: Building production-grade AI products with real user engagement
Senior Product Engineer Position Overview
The Senior Product Engineer position at Fonzi AI represents a premier opportunity to drive AI product innovation at the frontier of generative AI and large language models. You’ll join a curated network connecting elite engineers with 100+ pre-vetted startups backed by top-tier venture capital firms including Andreessen Horowitz, Sequoia Capital, General Catalyst, and Y Combinator. This role focuses on engineers who have demonstrated capability building AI-powered products end-to-end — not just prototypes, but production systems handling real users at scale. You’ll need fluency in retrieval mechanisms, memory architectures, agent frameworks, context engineering strategies, and comprehensive evaluation pipelines. This is for engineers combining strong software engineering fundamentals with deep awareness of cutting-edge LLM and agentic system developments.
As Senior Product Engineer, you’ll architect AI systems solving ambiguous problems in startup environments with small, focused teams. You’ll design retrieval-augmented generation systems, implement sophisticated agent frameworks, develop rigorous evaluation pipelines ensuring production reliability, optimize context engineering for maximum model performance, and integrate frontier LLM technologies into user-facing products. This is an exceptional opportunity for engineers with 2-8 years experience, ideally with background at high-growth companies. You’ll work with companies at seed through Series B stages, helping them scale from concept to production while navigating the rapidly evolving landscape of generative AI technology. Your expertise directly impacts startup success, user engagement, product innovation, and advancement of AI-powered solutions.
Why This Role Matters: As Senior Product Engineer at Fonzi AI, you build production AI systems changing how startups operate, develop retrieval and agentic systems handling real users, design evaluation pipelines ensuring production reliability, work with frontier LLM technologies at cutting edge, collaborate with exceptional founders and teams, solve ambiguous problems in fast-paced startup environments, advance AI career with innovation leader, and contribute to shaping future of generative AI applications.
Key Responsibilities & AI Product Development Duties
End-to-End AI Product Development & Architecture
- Build production-grade AI products handling real users at scale, not prototypes
- Design comprehensive AI system architecture for complex user problems
- Implement end-to-end product development from concept to production deployment
- Develop user-facing AI features with production reliability and performance
- Scale AI systems from startup MVP to production-grade reliability
- Integrate frontier LLM technologies into user-facing applications
Retrieval & Context Engineering Systems
- Design and implement sophisticated retrieval-augmented generation (RAG) systems
- Develop retrieval mechanisms optimizing information access for LLMs
- Engineer context engineering strategies maximizing model performance
- Implement semantic search and similarity-based retrieval approaches
- Optimize vector databases and embedding systems for production scale
- Develop memory management systems for multi-turn interactions
Agentic Systems & Agent Frameworks
- Architect agentic systems enabling autonomous decision-making capabilities
- Implement agent frameworks supporting complex reasoning and planning
- Design tool integration systems enabling agents to interact with external systems
- Develop multi-agent coordination and collaboration systems
- Implement feedback loops enabling agent learning and improvement
- Optimize agent reliability and production performance
Evaluation Pipelines & Quality Assurance
- Build comprehensive evaluation pipelines ensuring AI system reliability
- Develop rigorous testing frameworks for LLM-based products
- Implement automated quality assurance for AI-generated outputs
- Design metrics tracking AI system performance and user satisfaction
- Conduct systematic evaluation of retrieval and generation accuracy
- Establish production monitoring and performance tracking systems
Frontier LLM Integration & Optimization
- Stay current with cutting-edge LLM developments and emerging technologies
- Integrate latest LLM models and capabilities into products
- Optimize prompting strategies for maximum model performance
- Implement fine-tuning approaches for domain-specific applications
- Develop fallback strategies for model failures and edge cases
- Benchmark and evaluate different LLM options for specific use cases
Startup Collaboration & Problem-Solving
- Work effectively in startup environments with ambiguous problems
- Collaborate with founders and small teams on product vision
- Balance technical excellence with startup velocity and pragmatism
- Identify and solve critical technical blockers preventing user growth
- Iterate rapidly on product features based on user feedback
- Guide architectural decisions for long-term scalability
Qualifications & Requirements
Professional Experience
- 2-8 years software engineering experience building production systems
- Demonstrated experience at one or more high-growth companies
- Proven capability building end-to-end AI-powered products
- Track record shipping production systems handling real users
- Experience working in startup environments with ambiguous problems
AI/LLM Technical Expertise
- Fluency in retrieval-augmented generation (RAG) systems and implementation
- Deep understanding of memory architectures and context management
- Strong knowledge of agent frameworks and agentic AI systems
- Expertise in context engineering and prompt optimization
- Hands-on experience with comprehensive evaluation pipelines
- Deep awareness of cutting-edge LLM and agentic system developments
Software Engineering Fundamentals
- Strong software engineering fundamentals and best practices
- Proficiency in multiple programming languages (Python, TypeScript, etc.)
- Experience with system design and architecture at scale
- Knowledge of databases, APIs, and distributed systems
- Strong debugging and problem-solving capabilities
LLM Platform & Tool Experience
- Hands-on experience with leading LLM platforms (OpenAI, Anthropic, etc.)
- Familiarity with vector databases and embedding systems
- Experience with LLM frameworks and SDKs
- Knowledge of evaluation frameworks for LLM systems
- Understanding of prompt engineering best practices
Professional Skills & Attributes
- Excellent communication and collaboration abilities
- Comfort with ambiguity and ability to navigate uncertain environments
- Strong problem-solving and architectural thinking capabilities
- Genuine curiosity about AI and emerging technologies
- Startup mindset prioritizing speed and pragmatism
Career Development & Growth Opportunities
Technical Leadership
- Senior engineering role at AI innovation forefront
- Opportunity to lead AI product development initiatives
- Potential advancement to Principal Engineer or Technical Lead positions
- Exposure to cutting-edge AI research and emerging technologies
Learning & Development
- Continuous learning in rapidly evolving LLM and AI landscape
- Access to network of 100+ innovative startups and founders
- Opportunity to work with venture-backed founders and mentors
- Professional development in AI product strategy and leadership
About Fonzi AI — AI Recruiting & Innovation Platform
Fonzi AI represents an innovative AI recruiting platform revolutionizing how exceptional engineers connect with transformative early-stage startups. The company curates a network of 100+ pre-vetted startups backed by leading venture capital firms including Andreessen Horowitz, Sequoia Capital, General Catalyst, and Y Combinator. Fonzi operates offices in New York City and San Francisco, serving as a bridge between elite engineering talent and venture-backed founders building the future of technology. The platform identifies engineers who excel in startup environments, demonstrating capability to build production-grade AI products while thriving in ambiguous, fast-paced settings. Fonzi values genuine curiosity about AI, strong communication skills, and proven ability to ship products that matter.
Career Excellence at Fonzi AI: Join network of 100+ innovative startups backed by top-tier VCs, build production AI systems at cutting edge of LLMs and agentic AI, develop retrieval and context engineering expertise, work with exceptional founders and small teams, solve ambiguous problems in fast-paced startup environments, access mentorship from industry leaders, grow technical career in AI innovation, and help shape future of generative AI applications.
Who Should Apply?
- Product Engineers: With production AI system experience
- Full-Stack Engineers: From high-growth tech companies
- ML Engineers: With product and UX focus
- AI Researchers: Ready for product-focused roles
- Platform Engineers: With LLM and vector database expertise
- Startup Engineers: Seeking to scale AI impact
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