AI Engineer

What Success Looks Like in This Role

As an AI Engineer, you will be instrumental in the evolution of our in-house LLM powered chatbot systems. Your contributions will center around improving how our chatbot ingests, understands, and analyzes data using machine learning and modern NLP techniques. Your role will combine hands-on development, applied research, and collaboration with internal teams to deliver production-ready, intelligent solutions.

Key Focus Areas

• Technical Vision: Help shape and refine the long-term direction of our chatbot’s knowledge ingestion capabilities, ensuring alignment with business goals and advancements in AI.
• Hands-on Engineering: Take an active role in developing, optimizing, and maintaining knowledge ingestion pipelines and data monitoring infrastructure.
• Research & Experimentation: Explore and apply the latest developments in Retrieval-Augmented Generation (RAG), LLM evaluation, and prompt engineering techniques. Identify where cutting-edge methods can enhance our platform.
• Internal Learning Culture: Contribute to our internal ML knowledge base by actively participating in bi-weekly machine learning paper reviews and discussions with peers.

What You Bring to the Role

You will thrive in this position if you meet the following qualifications:

Professional Experience:

• Minimum of 3 years working on machine learning or data engineering projects.
• Proven success delivering production ready LLM based applications, with insight into deployment challenges, model tuning, and integration strategies.

Technical Competence:

• Strong Python programming skills, particularly in data manipulation using libraries like Pandas.
• Solid grasp of standard ML algorithms and the ability to apply them in real-world use cases.
• Familiarity with software engineering principles, clean code practices, and modular design.
• Strong understanding of algorithms and data structures to solve complex engineering problems efficiently.

Mindset & Communication:

• Quick to learn new technologies, frameworks, and ML research trends.
• Clear communicator with the ability to explain complex technical topics to both technical and non-technical stakeholders in fluent English.