Applied AI Engineer

We are seeking a highly skilled Software Engineer (with 6+ years of experience) with expertise in AI / ML (good to have : experience in Salesforce development will be preferred). This role focuses on designing and enhancing Salesforce applications by integrating advanced AI solutions, including Einstein GPT and custom models using Python or cloud platforms. Key responsibilities include building RAG pipelines, implementing real-time automation, and collaborating across teams to deliver scalable, secure, and high-performing solutions. This is a great opportunity for someone passionate about advancing enterprise AI beyond traditional tools.

Key Responsibilities :

Develop and deploy AI / ML models for real-time decision-making and automation.

Integrate AI / ML solutions into Salesforce CRM to enable intelligent data retrieval, personalized recommendations, workflow automation, forecasting, scoring, and opportunity insights.

Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and Large Language Models (LLMs) for improved contextual understanding within Salesforce workflows.

Good to have : Extend salesforce platform functionality using Apex (Triggers / Classes), LWC, Aura Framework, Visualforce Pages, Apex APIs and web services.

Good to have : Design, develop, test, document, and deploy Salesforce solutions based on business needs.

Enhance Salesforce applications with advanced AI features using both native (Einstein / Einstein GPT)

and external technologies (Python-based models or Azure / AWS ML services).

Build and maintain robust data pipelines for AI / ML workflows, including preprocessing, feature engineering, and integration of structured / unstructured data sources.

Posses a strong understanding of cloud platforms (AWS, Azure, GCP) and ability to optimize AI / ML workloads for high performance.

Manage CI / CD processes with Git to ensure efficient deployment of updates.

Collaborate with product managers, engineers, and data teams to identify opportunities for impactful AI-driven enhancements in the Salesforce ecosystem.

Ensure scalability, security / compliance (especially regarding sensitive customer data), reliability and performance of deployed models in production environments.

• Monitor model accuracy and relevance;

continuously improve user experience through feedback loops.