We are hiring an AI Engineer to design and operate production-grade AI/ML systems that directly improve product and operational outcomes. Our current focus is building an AI Agent Platform with a modular architecture: Gateway à Orchestrator à Agents → Tools → Guardrails → Feedback , enabling automation of complex workflows with strong control, validation and continuous learning. This role is intentionally broader than AI agents. Depending on priorities, you may also work on: Search and retrieval systems (keyword, semantic, hybrid) Recommendation, ranking and personalization systems AI evaluation, monitoring and reliability systems Other AI-powered product or operational systems with measurable business impact We are not looking for someone who only knows how to prompt models. We are looking for a strong engineer who can turn ambiguous problems into reliable systems in production . What You Will Build AI Agent Platform components: orchestration, agent coordination, tool usage, guardrails and feedback loops Search and retrieval systems using keyword, semantic or hybrid approaches Recommendation, ranking and personalization systems Backend services and APIs that expose AI capabilities safely and reliably Monitoring, evaluation and human-in-the-loop workflows for continuous improvement Responsibilities Design and build end-to-end AI/ML systems from problem definition to production rollout and iteration Develop and evolve AI Agent workflows, including context handling, tool calling, validation and fallback logic Build retrieval, search, ranking and personalization components that connect user intent to the right data or action Integrate LLMs with structured and unstructured data via context construction and tool-enabled workflows Implement monitoring, evaluation and guardrails to ensure quality, safety and reliability Design human-in-the-loop mechanisms for low-confidence or high-risk scenarios Collaborate with Product, Data and Engineering teams to translate business problems into practical solutions Proactively identify opportunities and improve systems beyond initial requirements 4+ years of experience in AI Engineering or ML Engineering Strong software engineering foundation with a production mindset, strong Python skills Experience building backend services and APIs Hands-on experience building LLM-based applications in production Solid understanding of: RAG, embeddings, vector databases Retrieval and search pipelines Experience in at least one of the following: AI agent or multi-step AI workflows Search, retrieval or relevance systems Recommendation, ranking or personalization systems Ability to reason about trade-offs across quality, latency, cost and reliability Ability to work through ambiguity and independently drive solutions Strong communication and cross-functional collaboration skills Nice to Have Experience with large-scale search or recommendation systems Experience with agent orchestration frameworks or tool-using LLM systems Experience with A/B testing, experimentation or evaluation pipelines Experience with observability, monitoring and production reliability Experience with multimodal systems (voice, OCR, image) Experience in high-scale operational domains (fintech, payments, customer operations) Experience mentoring or leading projects