Backend Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟬-𝟱𝟬 𝗟𝗣𝗔)

Experience: 2+ yrs

Location: Gurugram, Haryana, India

Job Type: Full-time

We are looking for a talented and hands-on AI/ML Engineer to contribute to the development of an omnichannel AI sales platform designed for the real estate industry. The role focuses on building intelligent systems that enable AI agents to engage prospects across voice calls, WhatsApp, SMS, email, CRM workflows, lead qualification, and campaign analytics.

The ideal candidate will have strong foundations in Artificial Intelligence, Machine Learning, Natural Language Processing, and data-driven application development. You will help build AI capabilities that automate customer interactions, understand leads, personalize conversations, and support real estate businesses in converting enquiries into meaningful sales opportunities.

Key Responsibilities

• Design, develop, test, and deploy AI/ML solutions for customer engagement and sales automation.
• Build intelligent systems for lead qualification, intent detection, customer segmentation, personalization, and recommendations.
• Develop and integrate conversational AI capabilities for voice and text-based customer interactions.
• Work with LLMs, NLP techniques, embeddings, vector databases, and retrieval-based architectures where appropriate.
• Build AI workflows for WhatsApp, SMS, email, voice, and CRM-driven customer journeys.
• Prepare, clean, transform, and analyze structured and unstructured datasets for AI/ML applications.
• Develop and evaluate machine learning models using appropriate metrics and experimentation techniques.
• Build data pipelines and processes required for model training, evaluation, and production inference.
• Improve AI agent accuracy, response quality, relevance, latency, and reliability.
• Implement mechanisms for monitoring model performance, data quality, failures, and AI-generated outputs.
• Integrate AI/ML models with backend services, APIs, databases, and application workflows.
• Conduct experiments and proof-of-concepts to evaluate new AI technologies and approaches.
• Collaborate with Product, Engineering, Data, and business teams to define AI requirements and deliver production-ready solutions.
• Troubleshoot model, data, integration, and production issues and implement sustainable improvements.
• Contribute to responsible AI practices, including data privacy, security, evaluation, and output quality.
• Document models, experiments, architectures, workflows, and technical decisions.
• Stay current with developments in Generative AI, LLMs, NLP, Machine Learning, and AI agent technologies.

What Makes You a Great Fit

• 2+ years of professional experience in AI/ML, Machine Learning Engineering, Data Science, NLP, or a related field.
• Strong understanding of Artificial Intelligence, Machine Learning, and data-driven application development.
• Strong programming skills in Python and experience with relevant AI/ML libraries and frameworks.
• Experience developing and deploying machine learning models in real-world or production environments.
• Strong understanding of NLP, text processing, classification, recommendation systems, or conversational AI.
• Hands-on exposure to Generative AI, LLMs, prompt engineering, embeddings, RAG, or AI agents is highly desirable.
• Experience working with structured and unstructured data and strong SQL/data-handling capabilities.
• Familiarity with vector databases, model APIs, cloud AI services, or ML deployment frameworks is an advantage.
• Understanding of model evaluation, experimentation, monitoring, and optimization.
• Experience integrating AI/ML capabilities with APIs, backend systems, databases, or SaaS applications.
• Strong analytical and problem-solving skills with a practical approach to building production solutions.
• Ability to work in a fast-paced environment and take ownership of AI/ML initiatives from experimentation through deployment.
• Strong communication and collaboration skills with technical and non-technical stakeholders.
• A Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field is preferred.