About Salesforce

Read all the information about this opportunity carefully, then use the application button below to send your CV and application. We’re Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. Position Overview As an Industries AI Engineer (Backend) with expertise in GenAI, Large Language Models (LLMs), and Prompt Engineering, you will drive innovation by designing, fine-tuning, and optimizing the use of LLMs for a variety of enterprise use cases. You will work at developing state-of-the-art solutions to transform how organizations leverage AI in their workflows. You will collaborate closely with Industries Application teams & bring their ideas to fruition. This role also involves building tooling that helps Salesforce Industries Application teams. This role demands a strong foundation in backend engineering, data science, natural language processing (NLP), and prompt engineering, with a focus on extracting the maximum potential from LLMs. You will collaborate across interdisciplinary teams to integrate cutting-edge AI technologies into Salesforce’s product ecosystem. Key Responsibilities Backend Development: Design, implement, and tune robust APIs and API framework-related features that perform and scale in a multi-tenant environment. Design and develop generic, customer-facing objects that promote both ease of use and customization. Test driven development practices as well as CI/CD tools and its usage. Prompt Engineering and Optimization: Design and experiment with creative prompts to optimize the performance of LLMs for specific use cases, ensuring accuracy, relevance, and efficiency. Implement techniques like few-shot learning, chain-of-thought prompting, and context tuning to enhance LLM outcomes. AI Model Evaluation and Deployment: Deploy LLM prompts into production systems, ensuring scalability, security, and efficiency. Problem Solving and Communication: Ability to translate business needs into AI solutions and communicate complex technical ideas to non-technical stakeholders. Proven experience working in cross-functional teams to deliver impactful results. Ability to effectively communicate and execute with geographically distributed teams. Experience in a fast-paced technical environment with changing priorities. Ability to develop and ship products in quick increments across multiple versions. Required Qualifications Educational Background: Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field. Technical Skills: Strong expertise in LLMs/MLMs (e.g., GPT, BERT, T5, Llama) and prompt engineering techniques. 5+ years of professional software development experience. High proficiency in Python and Java programming language. Experience in REST-based API development, API lifecycle management, and/or client SDKs development. Solid understanding of both relational and non-relational databases. Experience with developer tools such as Git and Jenkins. Demonstrated experience of working with ReST and thorough understanding of its fundamentals. Working knowledge of building B2B or B2C SaaS applications using cloud providers such as AWS, GCP, or Azure is desired. Broad knowledge of web standards relating to APIs such as REST, SOAP, XML, WSDL, HTTP, JSON, etc. Experience with Spring, gRPC, REST, and the HTTP protocol. Experience with Agile development methodology. Participate in the team’s on-call rotation to address complex problems in real-time and keep services operational and highly available. Office-Flex: work in-person three days per week. Preferred Qualifications Proficiency in Python and popular ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Prior experience in building AI solutions for enterprise software or SaaS platforms. Contributions to open-source NLP or AI projects.

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