Principal Consultant

Key Responsibilities:

We are looking for a Senior GenAI Application Engineer who operates effectively at the intersection of software engineering, GenAI application development, enterprise integration and production delivery. The successful candidate will help design, build and improve production grade GenAI applications that are reliable, observable, maintainable and useful to real enterprise users.

The successful candidate will:

1. Build and improve GenAI applications using frameworks such as LangGraph, LangChain or similar orchestration tools.
2. Work with open weight models, hosted LLMs and model serving patterns.
3. Develop agentic workflows, retrieval augmented generation, tool calling and prompt orchestration.
4. Integrate GenAI applications with enterprise systems, APIs, data sources and operational platforms.
5. Engineer solutions for production quality, including logging, tracing, evaluation, fallback behaviour and troubleshooting.
6. Bring a strong can do attitude, enthusiasm, curiosity and practical delivery mindset.

Requirements:

1. Should have 10 or more years of software engineering experience, preferably with recent hands on experience in GenAI application development.
2. Proven experience building production grade GenAI applications, not only prototypes, experiments or demos.
3. Strong hands on experience with LangGraph, LangChain or similar orchestration frameworks.
4. Practical understanding of RAG, agentic workflows, tool calling, prompt orchestration and context management.
5. Experience integrating LLMs into real applications using APIs, backend services and enterprise data sources.
6. Experience with open weight models or strong interest backed by hands on experimentation.
7. Strong backend engineering skills using Python, Java or similar languages.
8. Good understanding of API design, distributed systems and production resilience patterns.
9. Experience with observability, logging, tracing and troubleshooting for GenAI or backend applications.
10. Familiarity with containerised deployment environments such as Kubernetes or OpenShift.