AI Engineer

We are hiring AI Engineers at all levels, seeking individuals who have built and shipped production-grade AI Agents and have deep hands-on experience in Agentic AI.In this role, you will lead end-to-end development of autonomous AI agents that power our core media business. From architecting agentic workflows and RAG systems to deploying scalable, reliable LLM-powered products, you will play a central role in building the intelligent systems that enable audience growth, editorial excellence, and commercial innovation.This is a compelling opportunity to shape high-impact AI products, work alongside senior leadership, and bring Agentic AI into production at national scale.B. ROLES & RESPONSIBILITIESAgentic AI & Production AI AgentsDesign, build, and deploy production-grade AI Agents with capabilities in reasoning, planning, tool-use, memory, and multi-step task executionArchitect agentic workflows and orchestration frameworks (e.g. LangGraph, AutoGen, CrewAI or in-house) that are scalable, observable, and reliable at scaleBuild LLM-powered applications including RAG pipelines, autonomous research agents, content intelligence agents, and workflow automation agents for Editorial, Subscriptions, and AdvertisingAI Platform & InfrastructureDevelop the foundational platform for AI Agents - including agent registry, evaluation framework, prompt management, vector stores, memory layers, and tool integrationsBuild robust data pipelines and feature pipelines that feed AI Agents with high-quality structured and unstructured data from our data lake ecosystemImplement guardrails, safety checks, hallucination detection, and human-in-the-loop systems to ensure trustworthy and responsible AIAI Product DevelopmentOwn core AI products from prototype to production - audience intelligence agents, personalization agents, content generation and summarization agentsOptimize agents for latency, cost, accuracy, and user experience in a live production environmentPartner with Product, Editorial, and Commercial teams to translate ambiguous business problems into well-scoped agentic solutionsGovernance, Evaluation & ExcellenceEstablish evaluation metrics and observability for AI Agents - accuracy, faithfulness, task success rate, latency, and costChampion best practices in LLMOps, versioning, CI/CD for AI, and model governanceStay at the forefront of Agentic AI, LLMs, and multimodal models, evaluating practical applicability to SPH MediaC. WHO WE ARE LOOKING FOREducational QualificationsAn advanced degree (Master's or PhD) in Computer Science, AI/ML, Data Science, or a related quantitative fieldCandidates without a formal advanced degree who can demonstrate equivalent depth through a strong portfolio of production AI Agents are equally encouraged to applyTechnical ExperienceProduction Agentic AI : Minimum 3-6 years of hands-on experience building and shipping AI / ML systems, with at least 2+ years specifically building Production AI Agents. Proven track record of deploying Agentic AI systems with tool calling, function calling, planning & reasoning, memory, and multi-agent collaboration in production. Experience with LLM orchestration frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel or similarLLM & AI Stack: Strong hands-on experience with LLMs (OpenAI, Claude, Gemini, open-source LLMs), RAG architectures, vector databases (Pinecone, Weaviate, Milvus, pgvector), and embedding models. Experience fine-tuning, prompt engineering, and evaluating LLMs for production use cases. Experience with AI-powered solutions involving unstructured data - text, images, videoCore Engineering Skills: Deep proficiency in Python, and strong skills in SQL, Spark or similar data processing frameworks. Coding tests may be required. Experience building scalable APIs, microservices, and event-driven systems to serve AI Agents (FastAPI, Docker, Kubernetes)Solid understanding of MLOps / LLMOps, observability, and data governance best practicesFunctional Skills. Excellent communication skills with the ability to translate complex AI concepts for technical and non-technical stakeholders. Comfortable working in cross-functional, fast-moving environments where priorities evolve quickly. Experience in media, internet, or content-heavy industries is a strong advantage