ML), Brand Concierge

Adobe•San Jose, CA

52d

About The Position

We are seeking a creative and technically skilled Prompt Engineer to enhance large language model (LLM) performance across business-critical workflows. This position centers on designing, testing, and integrating strategies that drive intelligent agents and enterprise use cases. You will work closely with AI engineers, product teams, and domain experts to guarantee scalable, safe, and high-accuracy AI applications.

Requirements

3+ years of experience in NLP, AI/ML product development, or application scripting
Strong grasp of LLM capabilities and limitations (e.g., OpenAI, Claude, Mistral, Cohere)
Experience crafting prompts and evaluation methods for enterprise tasks
Familiarity with frameworks like LangChain, Semantic Kernel, or AutoGen
Strong ML, Python and API integration skills
Excellent written communication and structured thinking

Nice To Haves

Experience with LLM function calling, custom tool integration, and agent workflows
Background in UX writing, human-computer interaction, or instructional design
Understanding of enterprise compliance (e.g., SOC 2, GDPR) in AI systems
Bachelor's or equivalent experience in Computer Science, Computational Linguistics, Cognitive Science, or a related field

Responsibilities

Develop templates and multi-step chains tailored to specific business functions (e.g., sales enablement, support, knowledge management)
Develop few-shot, zero-shot, and hybrid patterns for enhanced reasoning and context retention
Maintain libraries for reuse and version control
Implement LLM function calling to trigger APIs, databases, or internal tools
Build tool-use pipelines within agent workflows for complex task automation
Define and build agent personas, roles, and behaviors for domain-specific applications
Manage multi-turn conversations, memory handling, and contextual continuity
Tailor prompts for performance in enterprise environments, prioritizing accuracy, privacy, fairness, and compliance
Collaborate with legal and security teams to mitigate hallucination, bias, and misuse risks
Partner with AI Agent Engineers to integrate prompts into agent workflows and orchestration pipelines
Maintain documentation and workflows for deployment in production environments