- 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).
experience
5 years
skills
Agentic AI, LLM, AI Development, AI Harness, Software Development
qualifications
no additional qualifications required
education
College/Pre-University