AI Engineer Lead/ Senior AI Engineer

ConnectedGroup Limited; Hong Kong; On-site; HKD 850,000 - 1,250,000; Full time

Job summary

ConnectedGroup Limited is seeking a hands-on Senior AI Engineer to design, build, and deliver production-grade AI solutions. You will bridge cutting-edge LLM architectures with enterprise applications, building core capabilities for an AI Agent platform and secure microservices.

You will implement RAG/GraphRAG, integrate AI tooling for testing and documentation, and ensure robust CI/CD, observability, and governance in production environments.

Qualifications

• 5+ years in software or AI engineering.

Responsibilities

• Design and build production-grade LLM solutions.

Skills

LLM applications

Prompt orchestration

Memory management

RESTful APIs

Docker/Kubernetes

CI/CD

Knowledge graphs

Education

Bachelor's degree in CS/Engineering or equivalent

Tools

LangChain

LangGraph

Vector databases

Docker

Kubernetes

Job description

Role Overview

We are seeking a hands‑on Senior AI Engineer to design, build, and deliver production‑grade AI solutions. You will build core capabilities for our AI Agent platform, engineer advanced retrieval mechanisms (RAG/GraphRAG), and develop secure microservices and APIs. Working closely with business stakeholders, product leads, and senior architects, you will bridge the gap between cutting‑edge LLM architectures and production‑ready enterprise applications.

Key Responsibilities

AI Agent & Solution Development: Design and build production‑ready LLM solutions, agentic workflows, task orchestration routines, and automated tools using Python and modern orchestration frameworks.

RAG & Knowledge Engineering: Implement and optimize enterprise Knowledge Augmentation solutions, leveraging RAG, GraphRAG, vector embeddings, and Knowledge Graph integrations.

AI‑Native Workflow Integration: Utilize and integrate AI coding tools (e.g., Cursor, Claude Code, Copilot) to streamline testing, documentation, and technical solution generation.

Runtime Quality & Governance: Implement evaluation protocols, logging, telemetry, access control, and guardrails to ensure AI models and agents perform accurately and securely in production.

CI/CD & Deployment: Apply robust engineering standards for testing, continuous integration/continuous delivery (CI/CD), containerization (Docker/Kubernetes), and cloud deployment.

Stakeholder & Team Collaboration: Partner with business analysts, QA, security, and risk teams to gather requirements, review code, and ensure solutions meet strict enterprise guidelines.

Production Support: Support application deployment, real‑time monitoring, troubleshooting, and iterative system performance enhancements.

Qualifications & Experience

Education: Bachelor's degree or above in Computer Science, Software Engineering, AI, Data Science, or equivalent practical experience.

Professional Experience: 5+ years in software engineering or AI engineering, with a proven track record of shipping scalable enterprise backend services or automation platforms.

Hands‑on expertise building LLM applications, prompt orchestration, function calling, memory, and evaluation frameworks.

Practical experience using LangChain, LangGraph, or equivalent LLM orchestration frameworks.

Direct experience implementing enterprise RAG, vector databases, or GraphRAG.

Engineering Best Practices: Solid understanding of microservices, RESTful APIs, database design, distributed systems, and security/privacy controls.

Cloud & DevOps: Hands‑on experience with Docker, Kubernetes, CI/CD, logging, and observability tools.