Prompt Engineer

Job summary

Bri*** is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.

Benefits

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, or a related field
• Six or more years of software engineering experience, with significant time on LLM-based applications
• Demonstrated experience shipping LLM-powered products to production
• Deep familiarity with modern LLM APIs and agent frameworks
• Strong understanding of retrieval-augmented generation, embeddings, and vector databases
• Experience designing evaluation pipelines for non-deterministic systems
• Strong Python
• Public writing, talks, or open-source contributions on LLM application development
• Experience with multi-agent architectures and complex tool-use systems
• Familiarity with fine-tuning workflows and when to choose them over prompting
• Exposure to product domains such as customer support, coding assistants, or analytics agents
• Experience integrating LLMs into enterprise software systems with strict compliance

Responsibilities

• Define organization-wide standards, patterns, and reference architectures for LLM-based applications
• Design prompt structures, instruction templates, and retrieval strategies for diverse production use cases
• Architect agentic systems incorporating tool use, planning, memory, and multi-step reasoning
• Lead the design of retrieval-augmented generation pipelines including chunking, indexing, and reranking strategies
• Develop evaluation frameworks for prompt quality, agent reliability, and end-to-end task success
• Build internal tooling and libraries that accelerate LLM application development across teams
• Establish guardrails, safety filters, and policy enforcement patterns for LLM-powered products
• Collaborate with model engineering teams on prompt-model co-design and fine-tuning opportunities
• Conduct technical reviews of LLM application designs across multiple product teams
• Mentor engineers and applied scientists on prompt engineering and LLM application architecture
• Lead red-teaming exercises and continuously improve robustness against adversarial inputs
• Track latency, cost, and quality trade-offs in LLM application design and recommend optimizations

Skills

Degrees

Industry

Company size