1. Prompt Design & Optimization

Develop and manage prompts for AI chatbots and agents across internal support, customer service, and data Q&A.
Optimize for accuracy, consistency, cost-efficiency, and safety.
Continuously test and improve prompts based on user feedback.

2. AI Use Case Implementation

Convert business needs into prompt designs and conversation flows, including system/user prompts and guardrails.
Support applications like data Q&A, knowledge assistants, automated insights, and customer support automation.

3. Collaboration with Data & AI Teams

Work with engineers and analysts to ensure model integration, data context, and business logic alignment.
Validate AI outputs and integrate prompts with data platforms and RAG pipelines.

4. Testing, Evaluation & Quality

Set criteria for relevance, clarity, and risk.
Test prompts in various scenarios and collaborate with quality teams for UAT and reliability.

5. Documentation & Knowledge Sharing

Document templates and best practices; maintain prompt libraries and versioning.
Help develop internal generative AI standards.

1. Education & Experience

Education: Bachelor’s degree in Computer Science, Software Engineering, Linguistics, or a related field with a heavy emphasis on logic and data.
Experience: 6 months to 2 years of experience. A strong portfolio showing advanced use of LLM APIs (OpenAI, Anthropic, etc.) is highly preferred.
Fresh graduates with strong academic projects or internships are welcomed

2. Technical skills

Prompt Mastery: Expert-level understanding of how different LLMs (GPT, Claude, Llama) react to different instructions and formatting (Markdown, JSON, XML).
Programming: Proficiency in Python (specifically for building AI wrappers and automating prompt testing).
AI Frameworks: Hands-on experience with LangChain, LangGraph, or Microsoft Semantic Kernel.
Data Skills: Basic SQL and an understanding of vector embeddings and semantic search.
Hands-on experience with LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face)
Comprehensive understanding of: Prompt patterns (system, role, chain-of-thought, few-shot) and Context management and grounding
Familiarity with Retrieval-Augmented Generation (RAG), Token limits and cost optimization strategies
Basic ability to read or write Python or similar scripting languages

3. Soft Skills

Linguistic Precision: An obsession with word choice, syntax, and clarity to minimize ambiguity in model instructions.
Analytical Thinking: A scientific approach to "debugging" prompts—identifying exactly why a model failed and how to pivot the instruction.
Curiosity: A drive to stay updated with the latest research papers on prompting techniques (e.g., from ArXiv).
Business & Communication Skills: Ability to understand business challenges and user intent, Clear written communication and documentation abilities and Skill in explaining AI behavior to non-technical stakeholders
Logical thinking and problem-solving mindset
Willingness to learn and adapt to new technologies
Ability to work well in a team environment

1. Career path development

2. Compensation & Benefits

3. Work Environment

Why Join Datatyk

Work on real enterprise analytics & AI projects
Specialized Expertise: Become a pioneer in Prompt Engineering, one of the most in-demand skills in the modern tech landscape.
Microsoft & AWS Partnership: Access to high-tier vendor resources and specialized AI training.
Innovative Projects: Build AI solutions that move beyond "chatbots" into real automated business logic.
Competitive compensation and flexible working environment

AI Engineer

Job Description