About Company:

Our client is a technology solutions provider specializing in enterprise software and digital platforms designed for the real estate and construction industry. The organization focuses on delivering innovative solutions that help businesses streamline operations, improve project management, and enhance customer engagement.

With strong expertise in areas such as ERP systems, CRM solutions, and data-driven platforms, the company supports developers and enterprises in optimizing their business processes. Backed by an experienced team of professionals, the organization is committed to delivering reliable technology solutions and driving digital transformation for its clients.

An Ideal Candidate:

The ideal candidate is an AI/ML professional with strong experience in Python, machine learning, and NLP technologies. The candidate should have hands-on experience working with Large Language Models (LLMs), RAG frameworks, and AI model development.

They should be capable of building and integrating AI models into applications, developing APIs, and working with SQL databases and cloud platforms. A good understanding of machine learning algorithms, deep learning frameworks, and data processing techniques is important.

The candidate should also have strong problem-solving abilities, good communication skills, and the ability to work collaboratively with technical teams to deliver AI-driven solutions.

Key Competencies:

1. Demonstrated ability to design, develop, and deploy AI/ML solutions using classical machine learning, deep learning, and generative AI techniques to solve complex business problems.

2. Proven expertise in building and integrating machine learning models such as lead scoring and price prediction systems with enterprise platforms like CRM and ERP.

3. Hands-on experience in designing and implementing Agentic AI systems, including autonomous agents, multi-step task execution, and tool orchestration for intelligent automation.

4. Strong experience in developing LLM-powered applications, AI agents, and RAG-based architectures using embeddings and vector databases to enable advanced information retrieval and decision support.

5. Ability to build NLP and OCR pipelines to extract structured insights from unstructured data sources such as emails, documents, images, and recorded conversations.

6. Strong knowledge of architecting scalable AI workflows and automation pipelines using cloud platforms to support high-performance and reliable deployments.

7. Experience in developing intelligent automation solutions using RPA for processes such as quote generation, approval workflows, and supplier data collection.

8. Proven capability to prototype AI-driven decision-support tools such as negotiation assistants that analyze pricing strategies, margins, and acceptance probabilities.

9. Solid understanding of MLOps practices including CI/CD for AI models, model monitoring, lifecycle management, and ensuring responsible AI implementation with strong data security and governance.

10. Excellent collaboration and communication skills with the ability to work closely with cross-functional teams, translate business workflows into AI-powered solutions, and mentor junior engineers while driving successful feature delivery.