HCLTech Analyst – Generative AI Hiring 2026: Eligibility, Skills and Application
HCLTech has listed an Analyst – Generative AI opportunity for engineering graduates with 0–3 years of experience, including fresh graduates. The vacancy appears on the company’s careers website under the title Analyst (Support & Operations), but its detailed job description focuses on building AI agents and contributing to AI/ML and large language model (LLM) applications.
The role is suited to candidates who have strong Python skills and can demonstrate hands-on work through academic assignments, internships or personal projects. Responsibilities include developing AI agents with LangGraph and LangChain, preparing data, assisting with model optimisation and working with senior team members on cloud AI platforms.
HCLTech Analyst – Generative AI: Job details
| Detail | Information |
|---|---|
| Company | HCLTech |
| Job title in description | Analyst – Generative AI |
| Title on careers portal | Analyst (Support & Operations) |
| Job reference ID | 166721 |
| Job band | E1 |
| Employment type | Full-time |
| Experience | 0–3 years, including fresh graduates |
| Qualification | Engineering degree |
| Locations listed | Noida, Hyderabad, Chennai, Bengaluru and Pune |
| Core programming skill | Python |
| Salary | Not disclosed in the supplied job description |
| Application deadline | Not specified in the supplied job description |
What will you do in this Generative AI role?
Develop AI agents
A key responsibility is developing AI agents using Python, LangGraph and LangChain on cloud AI platforms. This involves contributing to applications in which an LLM can work with defined tools or steps to complete a task.
Candidates should understand the difference between a basic chatbot and an application that connects a language model to tools, data or a multi-step workflow. The listing does not specify a particular cloud provider or a required model vendor.
Prepare and process data
The role includes collecting and preprocessing data for model training, evaluation and deployment. This makes Python-based data handling an important part of the work.
Relevant preparation includes working with structured data, identifying missing or inconsistent values, transforming inputs into an appropriate format and checking data quality before using it in an AI workflow.
Support model optimisation
The selected candidate will assist with optimising and fine-tuning AI models for performance, scalability and reliability. The description does not say that fresh graduates must independently train foundation models; it describes contributing to optimisation and fine-tuning activities.
Translate business needs into technical tasks
Team members will collaborate to understand business requirements and turn them into technical work. The role also involves learning from senior colleagues, keeping documentation up to date and following developments in Generative AI and AI/ML technologies.
These responsibilities make communication and the ability to explain technical decisions important alongside programming knowledge.
Eligibility criteria
According to the supplied job description, applicants should meet the following baseline requirements:
- Hold an engineering degree.
- Have 0–3 years of experience, with fresh graduates included.
- Demonstrate proficiency in Python.
- Have hands-on experience through academic, internship or self-initiated projects involving AI/ML algorithms or LLM-based applications.
- Be familiar with data processing in Python.
- Have familiarity with at least one relevant area such as deep learning, natural language processing (NLP), LLMs, or image segmentation and processing.
- Demonstrate problem-solving ability, willingness to learn and good communication skills.
Technical preparation: what candidates should demonstrate
A résumé listing AI keywords is less informative than a project that shows how those technologies were used. Candidates can prepare around the following areas.
Python programming: Be comfortable writing functions, working with data structures, handling exceptions and organising code into reusable components.
LLM applications: Understand the basic steps involved in sending input to a language model, handling the response and checking whether the output meets the application’s needs.
LangChain and LangGraph: The role explicitly mentions both frameworks. Candidates who have used them should be able to explain what they built and why they chose that approach. Familiarity should not be claimed solely from watching tutorials.
Data preparation and evaluation: Practise cleaning data, transforming inputs and defining how you would assess an application’s output. For LLM-based systems, consider how you would test factual accuracy, relevance and consistent behaviour.
Model and application reliability: Think through failure cases such as malformed inputs, unavailable services, slow responses or outputs that do not follow the expected format.
A project that can make your application more relevant
One useful portfolio direction is a small document-question-answering application. For example, you could create a tool that accepts a set of documents, retrieves relevant passages and generates an answer grounded in those passages.
A well-documented project could show:
- Python code and data-processing steps.
- An LLM-based workflow, with LangChain or LangGraph if you have genuinely used either framework.
- A method for retrieving relevant information.
- A few test questions with expected outcomes.
- Examples of incorrect or incomplete answers and how you handled them.
- Setup instructions and a clear explanation of the project’s limitations.
This is an example project idea, not a task assigned by HCLTech. A smaller, working project that you can explain thoroughly is preferable to an ambitious demonstration with unclear results.
Job locations
The description lists five possible locations:
- Noida
- Hyderabad
- Chennai
- Bengaluru
- Pune
The job page header also references Gautam Buddha Nagar, Uttar Pradesh, while the job summary lists the five cities above. Candidates should confirm the available location and work arrangement in the application portal or with the recruiter.
Salary and application deadline
The supplied official job description does not disclose a salary or CTC, and it does not state a closing date. Avoid relying on unofficial salary estimates as confirmed compensation for this specific requisition.
Since job listings can change, check the official page for the current vacancy status before submitting an application.
How to apply for HCLTech Analyst – Generative AI
Use the employer’s official application page:
Apply through HCLTech Careers – Job ID 166721
Before submitting, make sure your résumé clearly shows your Python experience, relevant AI/ML or LLM projects, data-processing skills and any hands-on exposure to LangChain or LangGraph. Include project links where appropriate, and describe your individual contribution accurately.
Is this role suitable for fresh graduates?
Yes. The supplied description explicitly includes fresh graduates within the 0–3 years of experience range. However, the role is not presented as a programming-only position: it asks for Python proficiency and practical AI/ML or LLM project experience.
Candidates who have built and tested a working AI application, can explain their design choices and understand the limitations of their solution may be able to demonstrate relevant experience even without previous full-time employment.
The key is to show practical understanding rather than simply listing Generative AI tools on a résumé.