ai platform engineer - up to rm 20k.

• Excellent Benefits
• Public Transport Accessible
• Career Growth

about the company

Randstad has partnered with a growing software solutions company, providing reliable and secure solutions for their clientele on a regional scale. Your future employers are seeking to build a strong, tech-savvy team that are capable of catering across various applications.

key responsibilities:

• Agentic System Development: Design and implement robust, autonomous Agentic AI workflows, including multi-agent orchestration, tool-calling interfaces, and complex reasoning loops.
• LLM Integration & Routing: Build scalable API layers, routing mechanisms, and middleware to seamlessly integrate foundational LLMs (e.g., OpenAI, Anthropic, LLaMA) into production applications.
• Harness & Guardrail Engineering: Develop strict input/output guardrails, fallback mechanisms, and validation schemas to ensure AI models behave predictably and securely in enterprise environments.
• Performance Optimization: Optimize the latency, throughput, and cost of LLM inferences. Implement advanced caching strategies, semantic routing, and context-window management (e.g., RAG pipelines).
• System Design & Architecture: Apply deep software engineering principles to AI systems, ensuring high availability, fault tolerance, and comprehensive observability (logging, tracing, and monitoring of AI outputs).
• Cross-Functional Collaboration: Partner directly with Product Managers, Data Scientists, and Frontend Engineers to translate product requirements into scalable AI-driven features.

requirements:

• Experience: 5+ years of professional experience in Software Engineering (Backend, Systems, or ML Engineering).
• Software Engineering Background: Deep expertise in core software engineering principles, including distributed systems design, microservices, CI/CD pipelines, automated testing, and scalable architecture.
• LLM Engineering: Proven hands-on experience building production applications using Large Language Models. Deep understanding of prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, and model evaluation techniques.
• Agentic AI Expertise: Demonstrated experience building Agentic AI systems capable of autonomous tool use, multi-step planning, and memory management.
• AI Model Knowledge: Strong familiarity with both proprietary APIs and open-source models (Hugging Face ecosystem), including how to deploy, quantize, and interact with them efficiently.
• Programming Languages: Expert-level proficiency in Python. Additional proficiency in Go, Rust, or TypeScript/Node.js is a strong plus.

nice to haves:

• Experience with AI orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, CrewAI).
• Familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, or pgvector).
• Experience with LLM observability and evaluation tools (e.g., LangSmith, Phoenix, TruLens).
• Background in cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

how to apply

Kindly click on the applicable link to apply if you are interested and suitable for this role. Alternatively, you can reach out to me via LinkedIn for a confidential discussion.

Sundar Ravindran | Randstad