Salesforce Developer

Job Summary:

We are looking for an innovative and technically skilled Generative AI Developer with 2–4 years of experience to join our team, focusing on the development and deployment of intelligent agents using Agentforce, Salesforce’s GenAI platform, or similar frameworks. The ideal candidate will be passionate about applying large language models (LLMs) to real-world business workflows, building conversational agents, and delivering high-impact AI-powered solutions within the Salesforce ecosystem and beyond.

Key Responsibilities:

• Design, develop, and deploy Generative AI agents using Agentforce, LLMs (like GPT-4), and related frameworks.

• Build and integrate intelligent, context-aware workflows into CRM, support, and operational systems.

• Collaborate with cross-functional teams (Product, Engineering, Data, and Business) to understand business challenges and deliver scalable AI solutions.

• Fine-tune and prompt LLMs for specific use cases such as market outreach, sales assistance, document summarization, and automation tasks.

• Maintain and optimize agent performance through evaluation, prompt engineering, and feedback loops.

• Stay up-to-date with the latest in generative AI, Salesforce AI tools (Einstein Copilot, Agentforce), and open-source frameworks.

• Create technical documentation and provide support for production deployments and ongoing enhancements.

Qualifications:

Required

• 2–4 years of experience in AI/ML or Software Development, with at least 1 year working directly with LLMs or GenAI applications.

• Hands-on experience with Agentforce, OpenAI, LangChain, or other GenAI frameworks.

• Proficiency in Python, JavaScript, or relevant programming languages for AI agent development.

• Experience integrating GenAI capabilities into Salesforce, web apps, or enterprise systems.

• Strong understanding of prompt engineering, vector databases, and agent orchestration.

Preferred

• Experience with Salesforce Einstein Copilot, Salesforce Data Cloud, or MuleSoft integration.

• Familiarity with LLMOps, model evaluation, or responsible AI best practices.

• Knowledge of REST APIs, OAuth, and cloud platforms (AWS, GCP, Azure).