Conversational AI Context Engineer

Conversational AI Context Engineer - CAICE

[Position code: CAICE ]

Superbo is seeking a CAI Context Engineer to join our Conversational Experience team. As we transition to advanced, pure-agentic AI solutions, this role is critical in bridging computational linguistics, conversation design, and technical implementation through prompt engineering. The successful candidate will combine linguistic insight, conversation design skills, and technical fluency (Python) to optimize and automate prompt design and agentic workflows.

This is mainly a hybrid role, with the need to both work-from-home (WFH) and visiting of customer premises.

What you will do:

·      Develop and refine sophisticated context modeling techniques, including:

• Prompt-level strategies
  (Chain-of-Thought, Few-Shot, ReAct, Prompt Chaining, etc.)
• Context tools and structures
  (roles, definitions, reasoning scaffolds)
• Memory architectures
  (short-term and long-term memory strategies)

·      Design and implement
Python-based automation and evaluation tools
to streamline prompt construction, iterate systematically, and validate outcomes.

·      Assist in designing, testing, and validating
agentic workflows
from a conversational user experience perspective, ensuring alignment with user needs and business objectives.

·      Collaborate with computational linguists, developers, and CX designers to evaluate the
effectiveness of context strategies
through analytical and qualitative assessments, employing iterative experimentation methodologies.

·      Maintain and continuously improve
guidelines, standards, and best practices
for context engineering within Superbo.

·      Proactively research emerging
context modeling and reasoning techniques
, bringing innovation into conversational agent design.

What you must have:

·      Bachelor's degree in Computational Linguistics, Computer Science, Linguistics, Cognitive Science, Data Science, or related fields.

·      Strong understanding and hands experience with prompt engineering techniques (CoT, Few-Shot, Zero-Shot, ReAct, Role-Based, etc.).

·      Proven experience working directly with Large Language Models (e.g., OpenAI GPT models, Claude, Gemini).

·      Familiarity with Retrieval Augmented Generation (RAG) techniques.

·      Familiarity with LLM application frameworks such as LangChain, LangGraph, or OpenAI Function Calling.

·      Comfortable working in Python

Nice to have:

·      Experience with LangSmith, LangFuse or similar observability tools for tracing, evaluating, and debugging LLM prompts and agentic workflows.

·      Experience measuring and optimizing Conversational Experience (CX) KPIs using tools like: TruLens, Ragas, Phoenix, or PromptLayer for LLM performance evaluation and feedback loops

·      Familiarity with conversation design, linguistics, NLP, AI systems design.

·      Analytical mindset with experience in iterative experimentation, validation, and optimization of AI-driven interactions.

·      Understanding of UX principles specific to conversational and agentic interfaces.

If you want to join a team of global leaders in their field, send your CV to 
.
ai

, referencing the position code. All applications will be treated in strict confidentiality. Only suitable candidates will be contacted
.