AI Engineer Internal Application

Key Responsibilities:

AI Solution Development:

• Develop and deploy AI models and algorithms to automate internal processes, enhance decision-making, and improve productivity.
• Build and fine-tune natural language processing (NLP) solutions for use cases such as document processing, chatbot development, and proactive insights.
• Create machine learning pipelines for predictive analytics and anomaly detection in operational workflows.

Integration and Deployment:

• Integrate AI models into existing internal applications, including CRM platforms, CLM systems, Employee-facing tools, Enterprise applications, Analytics tools and other custom inbuilt applications.
• Collaborate with DevOps teams to ensure efficient CI/CD pipelines for AI solutions.

Collaboration and Stakeholder Engagement:

• Partner with business stakeholders to identify pain points and opportunities for AI-driven enhancements.
• Work closely with IT and application development teams to align AI initiatives with organizational goals.

Data Management and Analysis:

• Leverage structured and unstructured data from multiple sources to train, test, and validate AI models.
• Implement data preprocessing pipelines to ensure data quality and completeness.

Performance Monitoring and Optimization:

• Continuously monitor and evaluate the performance of deployed AI models, ensuring accuracy, scalability, and efficiency.
• Optimize algorithms and infrastructure to reduce latency and improve user experience.

Innovation and Prototyping:

• Stay up-to-date with the latest trends and advancements in AI and machine learning to recommend and implement cutting-edge technologies.
• Rapidly prototype solutions for new business use cases, presenting proof-of-concept models to stakeholders.

Qualifications:

Education

• Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Experience

• 3 5 years of experience in AI engineering, machine learning, or data science roles.
• Proven track record of developing and deploying AI solutions in enterprise environments.
• Experience with CRM systems and automation platforms is a plus.

Technical Skills:

• Proficiency in programming languages like Python, R, or Java.
• Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.) and NLP libraries (SpaCy, Hugging Face, NLTK, etc.).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI tools (SageMaker, Vertex AI).
• Familiarity with APIs, microservices, and RESTful architectures.
• Strong understanding of data engineering concepts, including ETL pipelines and database management (SQL, NoSQL).

Soft Skills:

• Strong problem-solving and critical-thinking skills
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced environment and manage multiple priorities effectively