Top Prompt Engineering Jobs

Writes conversion-focused copy across paid ads, landing pages, email, direct mail, social media, and franchise assets. Designs generative AI prompt frameworks and libraries to scale content while maintaining brand voice and compliance. Conducts consumer research, develops copy variations, analyzes performance data, and collaborates with marketing, design, and brand teams on campaigns and customer journeys.

Designs, tests, optimizes, and documents large language model prompts for scalable healthcare conversation scoring. Collaborates with engineering, product, implementation, and data-labeling teams to improve scoring accuracy, prompt workflows, tooling, and standardization. Maintains a reusable prompt library, evaluates prompts using labeled datasets, and identifies process inefficiencies. The role requires strong LLM, NLP, and prompt-engineering knowledge, with preferred experience in data labeling, LangChain, OpenAI or GPT APIs, vector databases, linguistics, HCI, and Python automation.

Lead prompt engineering strategy, agentic workflows, LLM application architectures, reusable design patterns, evaluation frameworks, and developer tooling. Ship production LLM products, guide responsible AI practices, mentor engineers, and influence technical direction across enterprise teams.

Design and maintain prompt libraries, chaining strategies, tool schemas, guardrails, RAG integrations, and evaluation pipelines for multi-agent tutoring systems. Optimize model routing, cost, latency, reliability, safety, and schema compliance across Gemini and Claude models. Collaborate with AI, backend, product, and QA teams, debug production prompt failures, document experiments, and establish regression testing through CI/CD.

Develop, test, and optimize prompts for generative AI models and large language models. Analyze prompt performance, troubleshoot model behavior, and collaborate on AI solutions that improve mission workflows. Support model fine-tuning and Retrieval-Augmented Generation initiatives while researching advances in AI. The role includes structured prompt-engineering training before transitioning to client-facing work supporting U.S. Customs and Border Protection.

Develop and optimize prompts for generative AI and large language models supporting U.S. Customs and Border Protection. Test prompt variations, analyze results, troubleshoot model behavior, and collaborate on fine-tuning and Retrieval-Augmented Generation solutions. The role requires software development experience, programming skills, onsite availability in Ashburn or Washington, D.C., and the ability to pass a CBP background investigation.

Develop and optimize prompts for generative AI models and LLMs supporting U.S. Customs and Border Protection. Test prompt variations, analyze model behavior, support fine-tuning and RAG strategies, troubleshoot issues, and collaborate with technical teams to integrate AI solutions. The role requires software development experience, hands-on LLM experience, programming skills, and onsite availability in Ashburn, Virginia and/or Washington, D.C.

Develop and optimize prompts for large language models and generative AI applications supporting U.S. Customs and Border Protection. Responsibilities include testing prompt variations, analyzing model behavior, collaborating on process automation, supporting fine-tuning and RAG strategies, researching AI advancements, and debugging model issues. The role requires onsite work in Ashburn, Virginia and/or Washington, D.C., U.S. citizenship, and successful completion of a CBP background investigation.

Develops and optimizes prompts for generative AI models and large language models supporting U.S. Customs and Border Protection. Responsibilities include prompt testing, performance analysis, model behavior debugging, collaboration on AI process integrations, research into emerging techniques, and support for fine-tuning and RAG strategies. The role requires programming experience, hands-on LLM experience, prompt engineering knowledge, onsite availability in Ashburn or Washington, D.C., U.S. citizenship, and ability to pass a CBP background investigation.

Develops and optimizes prompts for generative AI and large language models supporting U.S. Customs and Border Protection. Responsibilities include testing prompt variations, analyzing model behavior, collaborating on AI integrations, researching emerging techniques, supporting fine-tuning and retrieval-augmented generation, and debugging model issues. The role requires software development experience, hands-on LLM experience, programming knowledge, prompt engineering familiarity, U.S. citizenship, and onsite availability in Ashburn or Washington, D.C.

Design, test, optimize, and debug prompts for large language models supporting federal border security missions. Translate mission requirements into reliable AI interactions, evaluate prompt variations, support fine-tuning and RAG strategies, and collaborate with cross-functional Agile teams to integrate AI solutions and streamline manual processes.

Designs, tests, and optimizes prompts for AI tools while creating and refining marketing and business content. Develops reusable prompt frameworks, ensures outputs match brand voice, fact-checks AI-generated content, and collaborates with marketing, sales, and operations teams. Continuously evaluates AI performance, stays current with prompt engineering techniques, and applies analytical judgment to improve content quality and effectiveness.

Supports stakeholders in applying Generative AI by designing and refining prompts, developing AI-enabled workflows, validating outputs, documenting use cases, researching emerging capabilities, and assisting with demonstrations, training, adoption, and implementation. The role translates business needs into practical AI solutions that improve mission and operational efficiency.

Develops AI proofs of concept for data management and enterprise architecture, analyzes business and technical artifacts, maintains metadata, evaluates data quality, supports governance and maturity initiatives, and develops ETL routines. The role collaborates with stakeholders and subject matter experts in an Agile environment to document AI use cases and apply analytical techniques to business and technical requirements.

Build and maintain AI-integrated software, services, scripts, and internal tools. Design and evaluate prompts, validate AI-generated outputs, implement safeguards, debug applications and API integrations, write tested and documented code, participate in code reviews and system design, and monitor AI feature performance. Apply AI safety, hallucination detection, and output evaluation practices while collaborating through Git-based development workflows.

Design, build, and optimize agentic AI solutions, including LLM prompts, agent workflows, MCP tools, tool-calling frameworks, RAG systems, and context orchestration. Develop evaluation methods, integrate enterprise systems and APIs, support deployment and monitoring, and ensure solutions meet security, governance, compliance, and responsible AI standards. The role is client-facing and involves collaboration across product, architecture, and engineering teams.

Paid part-time summer internship for a high school senior interested in AI prompt engineering and software development. The intern will learn Agile software delivery, use AI tools to support user stories and documentation, test software, identify bugs, participate in sprint activities, and collaborate with developers and stakeholders on secure mission-critical applications. No prior IT work experience or college degree is required.

Designs, tests, governs, and documents AI-assisted workflows for vulnerability and risk analysis in a federal cybersecurity environment. Responsibilities include structured prompt engineering, model parameter testing, hallucination reduction, prompt library management, quality validation, reproducibility benchmarking, and converting CISA cybersecurity workflows into standardized AI templates using enterprise Microsoft Copilot tools.

Design, maintain, and optimize encoding libraries and prompt-structure abstractions used across Anthropic. The role involves supporting multimodal data, running experiments on structured inputs, performing complex refactors, improving performance, and adapting systems for emerging AI research and production needs. The engineer will collaborate closely with researchers and engineers while maintaining intuitive APIs and enabling new encoding capabilities.

Design, test, and optimize prompts for Generative AI systems across customer support, content generation, workflow automation, knowledge management, and productivity use cases. Evaluate AI outputs for accuracy, tone, usefulness, and consistency; document findings and maintain prompt libraries and standards. Collaborate with AI engineers, product teams, data scientists, and business stakeholders to translate requirements into prompting solutions while researching emerging AI tools and methodologies.

Leads organization-wide prompt engineering strategy, standards, governance, and optimization. Designs advanced prompts and reusable libraries for enterprise AI applications, establishes evaluation benchmarks and quality processes, analyzes model outputs, and drives performance improvements. Partners with executives, product managers, engineers, and business stakeholders to translate requirements into AI solutions. Mentors prompt engineers, evaluates emerging AI platforms, and supports innovation and enterprise AI transformation initiatives.

Designs, tests, optimizes, and manages prompts for large language models and AI applications. Develops reusable prompt templates, evaluates AI outputs, conducts A/B testing, monitors performance, and improves accuracy, consistency, and business relevance. Collaborates with AI engineers, product managers, trainers, and business stakeholders to translate requirements into prompting strategies. Researches generative AI advancements and contributes to prompt engineering standards, evaluation methods, and responsible AI practices.

Supports stakeholders in identifying AI adoption opportunities, designing and refining prompts, building AI-enabled workflows, validating outputs, and implementing practical generative AI solutions. The role includes requirements gathering, workflow automation, RAG and agentic AI exploration, prototyping, documentation, demonstrations, user training, and collaboration with technical teams on deployment and integration.

Design, optimize, and iterate multi-turn conversational flows for text and voice agents. Craft persona-driven prompts and multilingual templates, test with recordings and simulations, analyze live interactions to reduce hallucinations and improve tone, and collaborate with PMs and engineers to integrate prompts, maintain a versioned prompt library, and ensure compliance and privacy.

Design, test, and document prompts and prompt libraries to optimize AI language model outputs. Collaborate with product, data, and ML engineers to integrate prompt solutions, run A/B experiments, measure performance, and maintain versioned documentation. Support TIBCO-specific implementation and stay current on AI/NLP techniques.