
Senior LLM Application Developer
5 days ago
We are seeking a seasoned expert to lead the development and implementation of Large Language Model (LLM) applications. This individual will be responsible for designing, building, and maintaining LLM systems, as well as creating comprehensive testing and evaluation suites to ensure agent reliability and measure model performance.
The ideal candidate will have strong Python proficiency, asynchronous programming skills, and experience with API development. They should also have hands-on experience building, productionizing, and maintaining LLM applications, including RAG systems, prompt engineering frameworks, evaluation pipelines, and agentic systems.
This is a core engineering role in a fast-scaling Industrial-AI startup that offers opportunities to work at the intersection of agentic AI, enterprise integrations, and large-scale production systems. The successful candidate will collaborate with a deeply technical founding team and innovation specialists to integrate cutting-edge model capabilities and deploy them in high-value customer environments.
Responsibilities- Design and implement LLM application lifecycle, including prompt engineering, model management, evaluation frameworks, and production monitoring.
- Develop and maintain core agentic SDK that powers multi-agent orchestration and tool-calling capabilities across enterprise systems.
- Build LLM operations infrastructure, including model serving, version control, A/B testing, and performance optimization pipelines.
- Create comprehensive testing and evaluation suites to ensure agent reliability and measure model performance against business KPIs.
- Collaborate with innovation team to integrate new model capabilities and optimize agent behavior for customer use cases.
- 3–5 years of software engineering experience with strong Python proficiency, asynchronous programming (Async IO), and API development skills.
- Hands-on experience building, productionising, and maintaining LLM applications, including RAG systems, prompt engineering frameworks, evaluation pipelines, and preferably, agentic systems.
- A strong understanding of LLM software development patterns, multi-agent orchestration, and tool-calling frameworks.
- Experience with LLM operations – model serving, monitoring, version control, and performance optimisation.
- Familiarity with evaluation methodologies, A/B testing, and metrics collection for ML systems in production.
- Bonus: experience with agentic frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen), MLOps tools, enterprise system integrations.
- A core engineering role in a fast-scaling Industrial-AI startup.
- End-to-end ownership of LLM application development with direct impact on real-world, mission-critical enterprise workflows.
- Opportunities to work at the intersection of agentic AI, enterprise integrations, and large-scale production systems.
- Collaboration with a deeply technical founding team and innovation specialists to integrate cutting-edge model capabilities and deploy them in high-value customer environments.
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