SnapCode Inc
Title:
AI Application/GenAI Engineer
Location:
Pleasanton, California (hybrid work)
We’re seeking a highly skilled
AI Application Engineer
to lead the architecture and execution of advanced LLM-driven systems, including prompt engineering pipelines, evaluation frameworks, RAG workflows, and LangChain-based orchestration. In this role, you'll design and test prompts for style, tone, and accuracy, implement rigorous A/B and statistical evaluation frameworks, and deploy LLM-powered features into production.
Responsibilities
Work cross-functionally with ML engineers, product managers, and backend teams to deliver scalable, prompt-driven solutions for enterprise applications.
Build retrieval-augmented generation (RAG) pipelines, develop prompt evaluation systems, and orchestrate LLM workflows with LangChain.
Apply deep prompt engineering expertise, practical Python development, and strong analytical skills to optimize prompt performance and user experience in real-world systems.
Qualifications / Required Expertise
3 - 6 years in AI/ML, NLP or GenAI roles.
Advanced knowledge of prompt engineering strategies and heuristics.
Proficient with LangChain (or similar), Python and API development.
Solid experience building RAG pipelines with vector databases.
Strong analytical mindset with an A/B testing and evaluation-driven approach.
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AI Application/GenAI Engineer
Location:
Pleasanton, California (hybrid work)
We’re seeking a highly skilled
AI Application Engineer
to lead the architecture and execution of advanced LLM-driven systems, including prompt engineering pipelines, evaluation frameworks, RAG workflows, and LangChain-based orchestration. In this role, you'll design and test prompts for style, tone, and accuracy, implement rigorous A/B and statistical evaluation frameworks, and deploy LLM-powered features into production.
Responsibilities
Work cross-functionally with ML engineers, product managers, and backend teams to deliver scalable, prompt-driven solutions for enterprise applications.
Build retrieval-augmented generation (RAG) pipelines, develop prompt evaluation systems, and orchestrate LLM workflows with LangChain.
Apply deep prompt engineering expertise, practical Python development, and strong analytical skills to optimize prompt performance and user experience in real-world systems.
Qualifications / Required Expertise
3 - 6 years in AI/ML, NLP or GenAI roles.
Advanced knowledge of prompt engineering strategies and heuristics.
Proficient with LangChain (or similar), Python and API development.
Solid experience building RAG pipelines with vector databases.
Strong analytical mindset with an A/B testing and evaluation-driven approach.
#J-18808-Ljbffr