AI Product Engineer

AI Product EngineerLocation: Mumbai – Work from OfficeExperience: 2–4 YearsEmployment: Full-timeMandatoryPlease complete the Google Application Screening Form (https://forms.gle/iqmA9QeSQuUHeSoC7)About Discovr AIDiscovr AI is building an AI-native infrastructure layer for creator advertising, enabling brands and agencies to automate creator discovery, campaign execution, content intelligence, brand safety, and reporting.We are building a new generation of AI systems for the creator economy, including specialised AI agents that can reason over creator data, campaign requirements, content, brand guidelines, and real-time signals.We are looking for an AI Product Engineer who wants to build these systems from the ground up.This is a highly hands-on engineering role.You will work closely with our product and engineering teams to design, build, test, deploy, and continuously improve the AI infrastructure and agentic systems powering Discovr AI.What You Will OwnDesign and build AI-powered features and intelligent agents for Discovr AI.Develop LLM-powered systems for reasoning, classification, extraction, recommendation, content analysis, and automation.Build agentic workflows that can perform multi-step tasks with tools, APIs, databases, and external systems.Experiment with different LLMs, models, prompting approaches, context strategies, and agent architectures.Build RAG pipelines, embeddings, retrieval systems, vector search, and knowledge systems.Develop robust prompt and model evaluation frameworks.Build systems for AI-generated and AI-assisted decisioning.Work with large volumes of creator, campaign, content, audience, and brand data.Integrate LLMs with internal databases, APIs, tools, and business workflows.Optimise AI systems for accuracy, latency, reliability, scalability, and cost.Build evaluation, monitoring, guardrail, and observability systems for AI agents.Work closely with Product Managers to convert product concepts into technically feasible AI systems.Rapidly prototype new AI capabilities and convert successful experiments into production systems.Debug and improve AI systems based on real-world performance.Contribute to the architecture and technical direction of Discovr's AI infrastructure.What We're Looking For2–4 years of strong software/AI engineering experience.Strong proficiency in Python.Strong understanding of LLMs and modern generative AI systems.Hands-on experience building applications using LLM APIs.Experience with AI agents, RAG, embeddings, vector databases, or LLM orchestration.Strong understanding of APIs, databases, backend systems, and distributed systems.Ability to write clean, scalable, production-quality code.Strong debugging and problem-solving ability.Strong understanding of software engineering fundamentals.Experience taking AI prototypes into production.Curiosity to experiment with emerging AI technologies and rapidly learn new frameworks.Strongly PreferredSignificant GitHub/open-source contributions.Strong personal AI projects.Active technical experimentation outside of work.Experience with LangChain/LangGraph or equivalent frameworks.Experience with OpenAI, Gemini, Claude, or other foundation models.Experience with vector databases and retrieval systems.Experience with model evaluation and observability.Experience with multimodal AI.Experience building autonomous or semi-autonomous AI agents.Competitive programming/coding background through platforms such as LeetCode, Codeforces, etc.The Ideal CandidateYou don't need to have worked on exactly the same problem before.But you should be the kind of engineer who sees a new AI capability and thinks:“Can I build this?”You should enjoy going deep into models, APIs, architectures, experiments, evaluation, and code.We are looking for someone who builds, not someone who simply follows AI trends.Why Join Discovr AI?Build production AI systems from the ground up.Work on complex agentic AI problems.Work closely with Product, Engineering, and Founders.Solve real-world problems across AI, advertising, creators, and large-scale data.High ownership over AI architecture and experimentation.Opportunity to work with rapidly evolving LLM and agentic technologies.