CRM and AI solutions engineer

18 hours ago

india Ritz Media World Full time

CRM Software Developer
1. Programming Languages:
Proficiency in backend languages like Java, C#, Python, PHP, or JavaScript (Node.js).
Knowledge of frontend technologies like HTML, CSS, JavaScript, and frameworks (React, Angular, or Vue.js).
2. Database Management:
Experience with SQL databases (MySQL, PostgreSQL, MS SQL) and NoSQL databases (MongoDB, Cassandra).
Understanding of data modeling, indexing, and performance optimization.
3. CRM Platform Knowledge:
Familiarity with popular CRM platforms such as Salesforce, Microsoft Dynamics, or HubSpot.
Experience in CRM customization, API integration, and module development.
4. API Integration:
Strong understanding of RESTful and SOAP APIs for integrating third-party services.
Experience with OAuth, JSON, XML for data transfer between systems.
5. Cloud Platforms:
Knowledge of cloud services like AWS, Google Cloud, or Azure, specifically tools for CRM and data management.
6. Data Analytics & Reporting:
Ability to implement data analysis tools within the CRM to help businesses gain insights.
Proficiency in using analytics tools like Google Analytics, Tableau, or Power BI.
7. Security Protocols:
Understanding of encryption, authentication, authorization, and other data security best practices.
Familiarity with GDPR and data privacy regulations.
8. UI/UX Design:
Basic knowledge of user experience and interface design to create intuitive CRM systems.
AI Integrated Tool Developer
1. Machine Learning & AI Algorithms:
Proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and Scikit-Learn.
Knowledge of algorithms for supervised, unsupervised, and reinforcement learning.
2. Natural Language Processing (NLP):
Experience with NLP libraries like NLTK, SpaCy, and Hugging Face for text-based AI tools.
Understanding of language models, sentiment analysis, and conversational AI.
3. Data Engineering:
Skills in data preprocessing, data cleaning, and feature engineering to prepare data for AI models.
Proficiency in handling large datasets and using tools like Apache Spark and Hadoop.
4. AI Development Languages:
Proficiency in Python (primary language for AI development), and possibly R or Julia for specific AI applications.
5. Deployment & Model Serving:
Familiarity with model serving techniques using Docker, Kubernetes, TensorFlow Serving, or Flask/FastAPI.
Knowledge of MLOps for continuous integration/continuous deployment (CI/CD) of AI models.
6. Cloud AI Services:
Proficiency in using cloud-based AI services like AWS SageMaker, Google AI Platform, or Azure AI.
7. API Development & Integration:
Ability to develop APIs for integrating AI models with other software tools or platforms.
8. Ethics & Compliance:
Understanding ethical implications, bias mitigation, and compliance with data regulations when implementing AI tools.
9. Visualization & Reporting:
Skills in using visualization tools to represent model outputs and data insights (Matplotlib, Seaborn, Plotly).
For both roles, strong problem-solving skills, attention to detail, and the ability to work collaboratively are also essential. Additionally, keeping up with the latest trends in CRM technology and AI development is crucial for innovation and effectiveness in these roles.

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