Zensar Technologies Hiring GEN AI – Prompt Engineering (Annotation) | Freshers Apply Now

Short Intro

Zensar Technologies is hiring fresh graduates for the role of GEN AI – Prompt Engineering (Annotation), a modern entry-level position aligned with the rapid adoption of Generative AI across industries. This role sits at the intersection of language, data, and artificial intelligence, making it highly relevant for freshers who are interested in AI systems but may not yet have deep coding experience.

Prompt engineering and annotation roles are becoming critical as organizations build and refine large language models, AI assistants, and enterprise AI workflows. In this position, candidates contribute directly to improving the quality, reliability, and relevance of AI-generated outputs by working with prompts, annotations, and structured evaluation processes. Freshers with strong analytical thinking, language clarity, and curiosity about AI systems will find this role a strong starting point in the evolving AI and analytics job market.

Job Highlights

Job Description

The GEN AI – Prompt Engineering (Annotation) role at Zensar focuses on improving how AI models understand, interpret, and respond to human inputs. Rather than building models from scratch, this role works on the quality layer of AI—how prompts are framed, how responses are evaluated, and how data is annotated to guide better outcomes.

As a fresher in this role, you will work with structured guidelines to review AI-generated outputs, label or annotate data, refine prompts, and support AI training pipelines. The business impact is significant: high-quality prompts and annotations directly influence accuracy, safety, and usefulness of enterprise AI systems. This role builds a strong foundation for future careers in AI analytics, data quality, applied AI, and even business-facing analyst roles.

Roles & Responsibilities

• Create, refine, and test prompts to guide generative AI systems
• Annotate text, responses, or datasets based on defined quality standards
• Evaluate AI outputs for relevance, correctness, and clarity
• Follow annotation guidelines to ensure consistency and accuracy
• Identify patterns or recurring issues in AI-generated responses
• Document feedback to help improve prompt strategies and datasets
• Collaborate with AI, data, and quality teams on improvement cycles
• Maintain confidentiality and data integrity during annotation tasks

Skills Required

Technical / Tool-based Skills

• Basic understanding of Generative AI and language models
• Familiarity with annotation tools or structured workflows (training provided)
• Comfortable working with large volumes of text or data
• Basic awareness of AI evaluation metrics and quality checks
• Willingness to learn prompt design techniques

Analytical / Business Skills

• Strong reading comprehension and attention to detail
• Ability to think critically about language and intent
• Clear written communication skills
• Process discipline and consistency in task execution
• Ability to interpret guidelines and apply them accurately

Eligibility Criteria

• Bachelor’s or Master’s degree from a recognized institution
• Freshers are eligible to apply
• Strong interest in AI, data, or analytics-related roles
• Comfortable working with structured processes and documentation
• Willingness to work in India-based teams

Salary Details

The estimated salary range for this role is ₹3 – ₹6 LPA, based on current market trends for entry-level AI annotation and prompt engineering roles. Final compensation may vary depending on academic background, skill alignment, and interview performance.

Selection Process (Expanded)

1. Application Screening
Profiles are reviewed for educational background, language proficiency, and interest in AI-related work.
Preparation tip: Highlight coursework, certifications, or self-learning related to AI, NLP, or data analysis.

2. Assessment / Task Evaluation
Candidates may be asked to complete a basic annotation or reasoning task.
Preparation tip: Practice evaluating AI-generated text for clarity and relevance.

3. Technical or Functional Interview
Focuses on understanding of AI concepts, prompt logic, and attention to detail.
Preparation tip: Be prepared to explain how you would improve a poor AI response.

4. HR Discussion
Covers role expectations, learning path, and organizational fit.
Preparation tip: Clearly communicate your interest in AI-driven careers.

What This Role Means in the 2025–2026 Job Market

Between 2025 and 2026, prompt engineering and annotation roles are becoming foundational across AI-driven organizations. As Generative AI systems scale, companies need human oversight to ensure quality, fairness, and usability. This has created strong demand for entry-level professionals who can bridge human language and machine outputs.

For freshers, this role offers a gateway into the AI ecosystem without requiring deep programming expertise on day one. Many professionals later transition into data analyst roles, AI quality specialists, or even business analyst interview preparation tracks after gaining experience. The skills learned here—critical evaluation, structured thinking, and AI understanding—are highly transferable across sustainability, analytics, and emerging tech roles.

Tips for Freshers

Understanding the Value of Prompt Engineering
Prompt quality directly affects AI accuracy. Learning this skill early positions you well for future AI-facing roles.

Build AI Literacy, Not Just Tools
Focus on how AI systems behave, their limitations, and ethical considerations.

Practice Structured Thinking
Annotation requires consistency. Train yourself to follow rules precisely.

Avoid Common Mistakes
Do not treat this role as “low impact.” Poor annotations can negatively affect entire AI systems.

Think Long-Term
Experience here can lead to roles in analytics, AI governance, or even sustainability and analyst jobs for freshers where AI-driven insights matter.

Helpful Resources

Generative AI Fundamentals
Source: Google AI Blog
Explains how generative models work.
Usage tip: Focus on understanding model behavior rather than code.

Prompt Engineering Guides
Source: OpenAI Documentation
Shows how prompts influence outputs.
Usage tip: Experiment with rewriting prompts for clarity.

AI Ethics & Quality
Source: World Economic Forum
Covers responsible AI practices.
Usage tip: Learn how human oversight improves AI trust.

Data Annotation Basics
Source: Towards Data Science
Explains annotation workflows.
Usage tip: Understand consistency and labeling standards.

Interview Insights

Interviewers typically assess clarity of thought, attention to detail, and understanding of AI behavior. Questions may involve reviewing sample AI responses, suggesting improvements, or explaining how prompts influence outputs. Freshers should focus on structured reasoning rather than technical jargon.

How to Apply

Candidates should apply through the official Zensar Technologies careers portal. Always rely on verified company communication for application updates.

About Company

Zensar Technologies is a global technology services and consulting organization known for its focus on digital engineering, data, and innovation-driven solutions. The company works with enterprises across industries to modernize systems, adopt emerging technologies, and improve business outcomes.

Zensar emphasizes continuous learning, structured career growth, and future-ready skills. For freshers, the company provides exposure to real-world projects, modern technology stacks, and collaborative teams—making it a strong platform to begin a career in AI, analytics, and digital transformation.

Disclaimer

This article is published for informational purposes only. We are not recruiters and do not charge any fees nor promote any third party to do so. Candidates must verify all job details from official Zensar Technologies sources. Do not pay anyone claiming to offer jobs or guaranteed selection, as such claims are fraudulent.