Prompt Engineer
Qapitol Qa
About the role
3 to 4 years of experience Core skills: LLM behaviour, prompt design, system instructions, few-shot examples, structured outputs, context management and prompt iteration. Technical skills: Python basics, JSON, API integration, basic SQL and understanding of tokens, context windows and model limitations. Tools: OpenAI API, Azure OpenAI, Anthropic APIs, prompt playgrounds, LangChain, basic evaluation tools and Git.
Quality skills: Test prompt variations, create test datasets, evaluate hallucinations, relevance, consistency and instruction adherence. Experience expectation: Develop reusable prompts and workflows for defined business use cases; document performance and failure cases. 58 years of experience Core skills: Advanced prompt/system design, multi-step workflows, structured generation, tool use, multimodal prompting and prompt versioning. Technical skills: Python, API integration, evaluation pipelines, dataset design and integration with RAG/agent architectures.
Tools: LLM evaluation frameworks, LangSmith, prompt/version management, tracing and observability platforms; model APIs and orchestration frameworks. Quality skills: Design repeatable benchmarks, adversarial test cases, regression tests and task-specific quality metrics. Experience expectation: Establish prompt engineering standards, improve reliability across models and collaborate with engineering, product and domain teams.
Recognized certifications AWS Certified AI Practitioner. Microsoft Certified: Azure AI Fundamentals (AI-900; verify current exam availability). Relevant cloud AI or generative AI credentials from AWS, Microsoft or Google Cloud.
Prompt engineering has no widely established professional certification standard. Practical evaluation results and a demonstrable portfolio are particularly important. explain this JD
Eligibility & process
Who can apply
Experience: 2-7 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
20 resourcesStudy material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Behavioural & HR questions 3
Highlight Qapitol Qa's market reputation, recent tech innovations, and how your skills in Artificial Intelligence directly solve their team's objectives.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package (Best in Industry)
Bengaluru, India
Experience: 2-7 Yrs. Open to matching quaโฆ
