AI Engineer

Seven Hills Consulting · Singapore

Sector
AI
Function
Product & Engineering
Level
Mid-Level
Employment type
Full Time
Posted
2026-08-24
Source
mycareersfuture

SPM Strategic is seeking an experienced AI Engineer to join our team responsible for building an internal AI CodeGen platform – a productivity accelerator used by engineering teams to automate code generation, testing, and more.

Your mission will be to build scalable, intelligent systems on top of LLMs that help developers focus on high-impact work by reducing manual effort. You’ll contribute to tools that generate code from designs, automate test cases, review code quality, and integrate deeply with GitHub, Jira, and IDEs.

Minimum Qualifications:

LLM Integration & Prompt Engineering: Experience building applications on top of GPT-3/4, Claude, or similar. RAG Systems: Hands-on expertise in Retrieval-Augmented Generation pipelines, vector stores, and semantic search. Cloud Infrastructure: Strong AWS experience (Lambda, S3, EC2, IAM); IaC with Terraform or CloudFormation.

Deep Technical Proficiency

Python & TypeScript/JavaScript (backend + integrations) PyTorch, Transformers, and HuggingFace Natural Language Understanding (NLU/NLP) for processing specs, wikis, and design inputs API Design, GitHub Webhooks, and VS Code extension APIs

Key Responsibilities

Design, develop, and optimize LLM-based services for code generation, test automation, and AI copilots. Implement RAG workflows to combine internal context (e.g., wikis, APIs, design specs) with LLM capabilities. Leverage agentic frameworks to enable AI systems to take intelligent actions (e.g., generate PR-ready code or suggest test coverage improvements). Collaborate with engineers, product managers, and platform teams to integrate solutions into VS Code, GitHub, and CI/CD pipelines. Own and evolve platform architecture, from prompt engineering to model orchestration and security compliance.

Preferred Experience

Productionizing AI copilots for internal developer workflows Contributing to open-source or internal AI agents/platforms Knowledge of engineering tooling or enterprise-grade compliance requirements

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AI TensorFlow Machine Learning Pipelines Test Automation Keras EC2 PyTorch