The current hiring announcement lists five openings: Talent Acquisition (3+ years), Software Development Engineer (2+ years), AI Engineer (4+ years), QA Engineer (2+ years), and QA Lead (6+ years). Candidates with relevant experience can share their updated resumes directly with the recruitment contact by email.
🏢 About AiSensy
AiSensy is a technology company focused on WhatsApp-based marketing, customer engagement, and business communication solutions. Its platform helps businesses use the WhatsApp Business ecosystem for customer messaging, marketing campaigns, notifications, and conversational engagement. Companies operating in this space work with integrations, APIs, messaging workflows, automation, and customer-facing software. These areas create opportunities for engineers and quality professionals to contribute to reliable products, scalable systems, and improved user experiences. For candidates interested in technology-driven environments, AiSensy may offer exposure to product development and business communication use cases.
📌 Job Overview
- Company: AiSensy
- Location: Gurugram, Haryana, India
- Positions: Talent Acquisition, Software Development Engineer, AI Engineer, QA Engineer, and QA Lead
- Talent Acquisition Experience: 3+ years
- Software Development Engineer Experience: 2+ years
- AI Engineer Experience: 4+ years
- QA Engineer Experience: 2+ years
- QA Lead Experience: 6+ years
- Application Method: Email your updated resume to tanu.priya@aisensy.com
💼 Available Positions and Career Opportunities
1. Talent Acquisition – 3+ Years This position may suit recruiters experienced in sourcing, screening, interview coordination, stakeholder communication, and recruitment pipeline management. Candidates who have hired for technical roles should highlight their ability to understand job requirements and engage suitable applicants. 2. Software Development Engineer (SDE) – 2+ Years This opportunity is relevant to software developers with experience in coding, debugging, data structures, APIs, databases, and software development practices. Depending on the team’s requirements, knowledge of backend systems, integrations, and scalable application design may be valuable. 3. AI Engineer – 4+ Years Experienced AI professionals can highlight their work in machine learning, generative AI, model integration, data processing, evaluation, and deployment. Practical project experience and the ability to explain technical decisions will help distinguish your application. 4. QA Engineer – 2+ Years This role may be suitable for professionals with experience in manual testing, functional testing, API testing, defect reporting, regression testing, and test automation. Candidates with experience validating web applications, integrations, and messaging workflows can emphasize relevant projects.
⭐ Why Are These Roles Good for Experienced Professionals?
- Career growth: The range of positions creates opportunities for candidates at different stages of their technology or recruitment careers.
- Product-oriented exposure: Engineering and QA professionals may gain experience with customer-facing software, APIs, integrations, and business workflows.
- Specialization: AI engineers can pursue AI-focused work, while QA professionals can deepen their expertise in automation, test strategy, and quality leadership.
- Cross-functional collaboration: Technology and recruitment teams both contribute to building and supporting a growing organization.
🧰 Skills Required as per Each Role
- Talent Acquisition: Technical sourcing, Boolean search, screening, applicant tracking systems, stakeholder management, and recruitment metrics.
- SDE: Programming fundamentals, data structures, algorithms, REST APIs, databases, debugging, Git, and software design.
- AI Engineer: Python, machine learning, deep learning fundamentals, LLMs, prompt engineering, model evaluation, APIs, and deployment practices.
- QA Engineer: Testing fundamentals, test case design, functional and regression testing, API testing, SQL, defect lifecycle, and Selenium or another automation tool where applicable.
🎯 Preparation Tips: Tailored to Each Opening
- AI Engineer: Be ready to explain an AI project end to end, including data preparation, model or LLM selection, evaluation, deployment, and limitations.
- QA Engineer: Prepare test scenarios for a messaging or API-driven application. Revise HTTP status codes, authentication, boundary-value analysis, SQL queries, and automation framework design.
- QA Lead: Prepare a case study explaining how you would build a test strategy, prioritize critical defects, improve automation coverage, and decide whether a release is ready. For every role, prepare concise examples of your personal contributions and measurable results rather than relying only on theoretical knowledge.
🧑💻 Expected Interview Rounds
- Round 1 – Recruiter screening: Experience, communication, role fit, notice period, and expectations.
- Round 2 – Technical or functional assessment: Coding for SDE, AI concepts for AI Engineer, testing concepts for QA, leadership scenarios for QA Lead, or sourcing expertise for Talent Acquisition.
- Round 3 – Practical or project discussion: A coding task, AI project walkthrough, test-design exercise, QA strategy discussion, or recruitment case study.
- Round 4 – Hiring manager or leadership discussion: Collaboration, ownership, problem-solving, and team fit.
- Final HR discussion: Compensation, availability, and employment details. The actual number and format of rounds may vary by role.
💰 Expected Salary Range
The official salary packages have not been disclosed. Compensation will depend on role, relevant experience, skills, interview performance, and the company’s current budget. Avoid treating generic online estimates as confirmed AiSensy salary bands. Ask the recruiter about the budgeted CTC, variable pay, benefits, and work arrangements before proceeding.
📄 Resume Tips to Improve Your Chances
- Use a role-specific resume: Apply for the position that best matches your experience rather than sending a generic profile.
- Show measurable impact: Include hiring metrics, software delivery results, AI project outcomes, automation coverage, defect reduction, or QA team achievements as appropriate.
- Highlight relevant tools: Mention only technologies and platforms you have genuinely used.
- Demonstrate ownership: Explain what you personally delivered, the challenges you solved, and the results achieved.
📩 How to Apply
Interested candidates can share their updated resumes directly with the recruitment contact below:
- Email: tanu.priya@aisensy.com
- Location: Gurugram
- Subject suggestion: Application – [Position Name] – [Years of Experience] Mention your preferred role, total relevant experience, current location, notice period, and contact details in your email. Attach a current resume tailored to the position. Important: Confirm the complete job description, work mode, compensation range, and interview process with the recruiter, as these details were not included in the original announcement.
Best wishes to everyone applying! 🚀
