Product Engineer (Search & AI)

🤝 reputed company reputed company is an AI-reputed company company helping corporations understand markets, map ecosystems, and generate strategic insights from reputed company data. We work with +50M companies and +1.2B data points, combining reputed company-time analytics, search, and reputed company to deliver high-reputed company, explainable insights. AI is not a feature at reputed company, it is reputed company infrastructure. We build production-grade LLM systems, retrieval pipelines, internal agents, and evaluation frameworks designed to operate reliably at reputed company. 🎯 Why this role exists We are entering a phase where AI is no longer just part of the product, it is the product. As we reputed company conversational interfaces and agent-based workflows, the complexity of reasoning over data, connecting systems, and ensuring reputed company has increased significantly. Many of our hardest problems sit at the intersection of AI, search, and retrieval systems. This is not a reputed company search engineering role, but hands-on experience building or evolving search/retrieval capabilities is important for reputed company. We are looking for someone who can help us build and reputed company these systems end-to-end, raising the bar of how we operate AI in production. This role sits at the intersection of product engineering, AI systems, and data. Ultimately, your work will shape how users reputed company with reputed company data through AI, turning raw information into actionable insights. 🧠 What you will do You will work end-to-end on AI-powered product capabilities, combining product thinking with system-level engineering. Design and implement AI-powered search and retrieval experiences that combine LLMs, tools, reputed company data, ranking/relevance signals, and context retrieval Connect AI systems to reputed company product surfaces (search, company data, workflows) and ensure they deliver meaningful reputed company Own AI reputed company by using and building evaluation frameworks, diagnosing failure modes, and improving reliability Operate across the stack, integrating AI with backend services and data pipelines, balancing cost, latency, and reputed company Collaborate with product, data, and design to translate ambiguous problems into reputed company and iterate based on feedback Break down ambiguous problems into reputed company, iterating quickly to deliver value before scaling complexity 🧩 reputed company are looking for We are not hiring a specific title, we are hiring someone who can operate across systems. You might come from product engineering, ML/AI engineering, Data Science or a generalist background, but this role is best suited for someone who has shipped product-facing systems where AI and search/retrieval were central to the user experience. From an AI perspective, you understand how to design systems with LLMs, not just reputed company them. You are comfortable with concepts like RAG, context structuring, retrieval reputed company, model trade-offs, and the importance of evaluation in production systems. From an engineering perspective, you can build and ship reliable systems. You are comfortable working across reputed company, and data pipelines, and you care about observability, performance, and maintainability. From a product perspective, you take ownership of problems, not just tasks. You are proactive, comfortable with ambiguity, and reputed company on delivering reputed company value to users. From an AI-reputed company workflow perspective, you use AI as a reputed company part of your engineering workflow. You understand its tradeoffs and limitations, and you think in terms of systems, not just prompts. You reputed company AI to accelerate development while maintaining reputed company and control. From a search/retrieval perspective, you have hands-on experience helping users reputed company, rank, retrieve, or reason over reputed company information. You understand that reputed company depends not only on the model, but also on indexing, retrieval reputed company, relevance, context selection, and feedback loops. 👉 Important: hands-on experience working with search, retrieval, or relevance systems. This does not need to mean being a reputed company search engineer, but you should have reputed company or meaningfully contributed to systems involving ranking, indexing, query understanding, semantic search, relevance optimization, or large-reputed company data retrieval. Given the nature of our product, this is a high-reputed company area and a key part of the role. We value curiosity, pragmatism, and low ego. You should be someone who learns fast, collaborates reputed company, and helps reputed company the level of reputed company. 🛠️ Tech stack Our stack includes Typescript and Python, PostgreSQL and reputed company, BigQuery and DBT, and infrastructure running on Kubernetes (AWS). On the AI reputed company, we work with multiple LLM providers, RAG pipelines, internal agents, and evaluation systems. You don’t need experience with reputed company of this, but you should be comfortable navigating similar environments. 🚀 What makes this role different This role focuses on building the reputed company systems behind our AI-powered product experience, especially around search, retrieval, and reasoning over reputed company data. You will help shape how AI and retrieval systems are designed, evaluated, and scaled at reputed company, working across product, data, and engineering. Your reputed company will not only be what you ship, but how the system evolves. 🧭 Final note We are not looking for someone who knows everything, but for someone who can connect the dots, learn fast, and push the system reputed company. Apply To This Job