Senior AI Engineer

About Company:

Our client is a growing IT services and technology solutions provider specializing in software development, web and mobile applications, and digital solutions. The company focuses on delivering reliable and scalable technology solutions to businesses across various industries. With a team of skilled professionals, the organization is committed to providing quality services, innovative solutions, and strong customer support while continuously expanding its capabilities in the technology space.

An Ideal Candidate:

The ideal candidate is a skilled AI/ML professional with 4–6 years of hands-on experience in building and deploying machine learning and NLP solutions. The candidate should have strong Python programming skills and experience working with ML/DL frameworks and LLM-based applications.

They should have practical knowledge of RAG architectures, vector databases, OCR/NLP pipelines, and cloud platforms. The candidate should be able to develop scalable AI solutions, work with cross-functional teams, and contribute to automation and AI-driven business processes. Strong problem-solving, communication, and collaboration skills are essential for success in this role.

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.