We are a group of Generative AI Application Engineers who are passionate about designing products and building intelligent agents that work alongside humans to drive customer success 24/7. We love to learn, teach, and help each other, and we seek individuals with a collaborative attitude and openness to others' ideas.

You will play a critical role in integrating generative AI, building citations and guardrails for LLMs into Agentforce, and using the latest LLM algorithms and technologies to build the next wave of intelligent agents. You will participate in the end-to-end AI product development lifecycle, designing and developing scalable generative AI systems and services. You will collaborate with AI Platform Engineers and Software Engineers to define requirements and develop reusable workflows and ML pipelines.

• Build and own end-to-end scalable services that can be integrated with numerous applications, support thousands of tenants, and operate at scale in production.
• Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
• Participate in periodic on-call rotations and be available to resolve critical issues.
• Collaborate with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production.

• 3+ years of industry experience in ML engineering, building AI systems and/or services.
• Bachelors (or) Masters degree in Computer Science, Software Engineering, or related STEM field with strong competencies in algorithms, data structures and software design.
• Experience with distributed, scalable systems and modern data storage, messaging, and processing frameworks, such as Kafka, Spark, Docker, and Hadoop.
• Strong programming skills in Python, with experience in building ML pipelines
• Proven ability to innovate and deliver results at scale.
• Basic understanding of deep learning and machine learning algorithms.
• Experience with LLMs and prompt engineering.
• Proven experience building and applying machine learning models to business applications.
• Expertise in applying LLMs, prompt design, and fine-tuning methods.
• Excellent problem-solving skills; the ability to tackle problems the world has yet to solve.

• Expertise in retrieval systems and search algorithms.
• Familiarity with vector databases and embeddings.
• Experience developing applications/services for complex business use cases and large amounts of unstructured data.
• Experience with conversational AI.
• Strong written and verbal communication skills.
• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams.