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 clients 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 & RESPONSIBILITIES

Agentic AI & Production AI Agents

• Design, build, and deploy production-grade AI Agents with capabilities in reasoning, planning, tool-use, memory, and multi-step task execution
• Architect agentic workflows and orchestration frameworks (e.g. LangGraph, AutoGen, CrewAI or in-house) that are scalable, observable, and reliable at scale
• Build LLM-powered applications including RAG pipelines, autonomous research agents, content intelligence agents, and workflow automation agents for Editorial, Subscriptions, and Advertising

AI Platform & Infrastructure

• Develop the foundational platform for AI Agents - including agent registry, evaluation framework, prompt management, vector stores, memory layers, and tool integrations
• Build robust data pipelines and feature pipelines that feed AI Agents with high-quality structured and unstructured data from our data lake ecosystem
• Implement guardrails, safety checks, hallucination detection, and human-in-the-loop systems to ensure trustworthy and responsible AI

AI Product Development

• Own core AI products from prototype to production - audience intelligence agents, personalization agents, content generation and summarization agents
• Optimize agents for latency, cost, accuracy, and user experience in a live production environment
• Partner with Product, Editorial, and Commercial teams to translate ambiguous business problems into well-scoped agentic solutions

Governance, Evaluation & Excellence

• Establish evaluation metrics and observability for AI Agents - accuracy, faithfulness, task success rate, latency, and cost
• Champion best practices in LLMOps, versioning, CI/CD for AI, and model governance
• Stay at the forefront of Agentic AI, LLMs, and multimodal models, evaluating practical applicability to SPH Media

C. WHO WE ARE LOOKING FOR

Educational Qualifications

• An advanced degree (Master's or PhD) in Computer Science, AI/ML, Data Science, or a related quantitative field
• Candidates without a formal advanced degree who can demonstrate equivalent depth through a strong portfolio of production AI Agents are equally encouraged to apply

Technical Experience

Production 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 similar

LLM & 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, video

Core 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 practices

Functional 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