Software Engineering SMTS (Salesforce Exp Mandatory)

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Role Overview
Learning Technology team at Salesforce is looking for a AI Engineer (SMTS) to join our Agentforce implementation team. This position requires an individual with strong AI technology knowledge, technical prowess, As an engineer with expertise in using Large Language Models (LLMs), Prompt Engineering and Salesforce Agentforce you will drive innovation by designing, fine-tuning, and optimizing the use of Agentforce Agent for a variety of enterprise use cases.
This role demands a strong foundation in 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.
Partner with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production

Key Responsibilities
 

Prompt Engineering and Optimization:

• Design and experiment with creative prompts to optimize large language models (LLMs) for specific uses, focusing on accuracy and efficiency.
• Use techniques like few-shot learning, chain-of-thought prompting and context tuning to improve outcomes.
• Refine prompt templates continuously with data insights, A/B testing, and user feedback for better performance and satisfaction.
• Use pre-trained LLMs (e.g., GPT, Llama, Falcon) for Salesforce-specific applications using prompt engineering and reinforcement learning from human feedback (RLHF).
• Build and maintain datasets for training, fine-tuning, and evaluating LLMs for various use cases.

Design :

• Create prompt templates and conversational AI experiences for diverse use cases, such as issue resolution, customer onboarding, and learning.
• Develop multimodal interaction designs incorporating text, voice, visual, and sensory inputs to craft rich, human-like user experiences.
• Design conversational flows for autonomous agents capable of completing complex tasks (e.g., lead qualification, customer support, order processing) independently or semi-independently.
• Establish best practices, guidelines, and documentation to standardize team conversational design processes.
• Applying behavioral psychology principles to drive user engagement.
• Incorporating accessibility standards into conversational and multimodal AI designs.
• Tailor AI interactions to reflect tone, style, and cultural nuances across customer segments and industries.
• Champion accessibility and inclusivity, ensuring AI designs meet diverse user needs and industry standards.

AI Model Evaluation and Deployment:

• Develop metrics and tools to evaluate model performance, reliability, and fairness.
• Deploy LLM prompts into production systems, ensuring scalability, security, and efficiency.

Data Science and Insights:

• Analyze large-scale datasets to uncover patterns, insights, and opportunities for AI applications.
• Ensure data quality, security, and compliance with industry standards.

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 ease of use and customization.

Collaboration and Research:

• Collaborate with product managers, engineers, and designers to identify and implement AI-driven solutions.
• Stay at the forefront of LLM research and emerging technologies to recommend and integrate advancements into Salesforce's AI strategy.
• Participate in the team's on-call rotation to address complex problems in real time and keep services operational and highly available.

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.
• Experience in a fast-paced technical environment with changing priorities and executing with geographically distributed teams.
• Ability to develop and ship products in quick increments across multiple versions

Required Skills:

• Bachelor's degree in Computer Science, Software Engineering, or equivalent experience.
• 6+ years of industry experience in ML engineering, specifically in building AI systems and/or services.
• Strong experience with large language models (LLMs) and prompt engineering.
• Proven ability to build and apply machine learning models for business applications.
• Experience in conversation design, UX writing, or related fields, with a strong portfolio of AI-driven projects.
• Proven ability to design scalable conversation flows, user journeys, and AI prompt templates.
• Expertise in multimodal interaction design and generative AI technologies (e.g., GPT or similar models)

Programming Skills:

• Good working knowledge of deep learning and machine learning algorithms, with experience in machine learning frameworks such as TensorFlow and PyTorch.
• Strong background in natural language processing (NLP) and AI applications across various industries, such as sales, service, and commerce.
• Experience with reinforcement learning techniques such as RLHF.
• Knowledge of model interpretability, bias mitigation, and ethical AI practices.
• Proficiency in Python and popular ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
• Prior experience building AI solutions for enterprise software or SaaS platforms.
• Understanding of both relational and non-relational databases.
• Experience in REST-based API development, API lifecycle management, and client SDK development.

Salesforce Expertise:

• Proficient in APEX, Java, Python
• Hands-on experience in Salesforce Administration and various Salesforce cloud products such as Sales Cloud, Service Cloud, Experience Cloud, and Data Cloud.
• Experience with Salesforce configuration changes, including (but not limited to) flow, assignment rules, approval processes, fields, page layouts, record types, dynamic layouts, apps, actions, custom settings, mobile administration, and dashboards/reports.
• Familiarity with developing in an enterprise environment, including source code control, IDE, continuous deployment, and release management (Git, Eclipse, CircleCI, VSCode).

Personal Qualities:

• Adaptable and organized under pressure.
• Strong problem solver with technical and troubleshooting skills.
• Proven history of tackling complex challenges effectively.
• Skilled at fostering collaboration between technical and business teams.
• Able to prioritize tasks in fast-paced environments.
• Excellent interpersonal skills for collaborating with cross-functional teams and influencing stakeholders.
• Capable of translating complex concepts into actionable strategies.
• Strong analytical and problem-solving expertise.

Preferred Knowledge:

• Functional and technical knowledge of any Learning Management System or Certification Management System is strongly preferred.

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