The position is responsible for the development and maintenance of Salesforce applications and will be working with other engineers and developers on different layers of the infrastructure.
Job Description
Responsibilities include:
Develop solutions in Salesforce and related systems for business use cases.
Utilize strong design and development patterns and frameworks to ensure solutions are sound and meet requirements.
Follow good practices and project guidelines in all cases including the use of source code control, automated testing and deployment approaches, test-case-based development, and proper documentation practices.
Contribute to the development team by sharing knowledge, assisting others, and keeping up with the new trends and best practices as they evolve in the industry.
Identify and quickly escalate potential issues with design, packaged software, client resources, or anything else that impacts your ability to deliver according to expectations.
Specializes in retrieval-augmented generation architecture — building the search, indexing, and retrieval layer that grounds LLM outputs in accurate, up-to-date information.
Works on pretraining and post-training of foundation models — architecture experiments, training efficiency, alignment techniques (RLHF, DPO), and scaling research, often in collaboration with research scientists.
Owns model development, training, and quality — building and improving the ML models (not just LLM wrappers) that power a product, from data pipeline to production deployment.
Owns the compute infrastructure that trains and serves AI models — GPU cluster management, distributed training pipelines, and inference serving at scale. A natural pivot for DevOps/backend infra engineers.
