Darwin Resources
Open AI Solution Engineer
– Seattle, WA (Hybrid). Join our solutions organization to design, build, and deploy OpenAI-powered solutions for enterprise clients.
Key Responsibilities
Collaborate with Sales, Product, and Engineering teams to understand client requirements and design scalable OpenAI-driven solutions.
Develop and deliver customized technical demos, proof‑of‑concepts, and prototypes using OpenAI APIs and ecosystem tools.
Advise clients on best practices for integrating LLMs into their existing technology stacks, including data pipelines, APIs, and front‑end applications.
Guide clients through technical architecture decisions, deployment strategies, and performance optimization.
Provide post‑sale technical support and solution implementation, ensuring a smooth transition from proof‑of‑concept to production.
Maintain expertise in OpenAI's product suite and stay current on industry trends in generative AI, LLMs, and natural language processing.
Required Qualifications
3+ years in a Solutions Engineer, Sales Engineer, ML Engineer, or similar technical role.
Proficiency with Python, REST APIs, and common ML/AI libraries (e.g., Hugging Face Transformers, LangChain, OpenAI SDK).
Experience designing or deploying applications that utilize LLMs, embeddings, and RAG architecture.
Strong understanding of software architecture and integration patterns, especially within cloud environments (AWS, Azure, or GCP).
Excellent communication and stakeholder engagement skills, with the ability to explain complex topics to technical and non‑technical audiences.
Tools & Skills
OpenAI API (GPT‑4, GPT‑4o, DALL‑E, Whisper)
Prompt engineering, Retrieval‑Augmented Generation (RAG)
LangChain, LlamaIndex, vector databases (Pinecone, FAISS, Weaviate)
Python, FastAPI, front‑end integration
Knowledge of token limits, context management, cost optimization
Focus
Create custom GPT on a daily basis.
Specialize in using OpenAI's foundation models (e.g., GPT‑4, DALL‑E, Whisper).
Build applications and products powered by pre-trained LLMs rather than training models from scratch.
Typical Work
Use OpenAI APIs (chat, completion, embeddings, vision, audio) to build intelligent systems.
Design complex prompt workflows (prompt engineering, few‑shot learning, prompt chaining).
Integrate LLMs into apps for tasks like summarization, search, agents, chatbots, code generation, etc.
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– Seattle, WA (Hybrid). Join our solutions organization to design, build, and deploy OpenAI-powered solutions for enterprise clients.
Key Responsibilities
Collaborate with Sales, Product, and Engineering teams to understand client requirements and design scalable OpenAI-driven solutions.
Develop and deliver customized technical demos, proof‑of‑concepts, and prototypes using OpenAI APIs and ecosystem tools.
Advise clients on best practices for integrating LLMs into their existing technology stacks, including data pipelines, APIs, and front‑end applications.
Guide clients through technical architecture decisions, deployment strategies, and performance optimization.
Provide post‑sale technical support and solution implementation, ensuring a smooth transition from proof‑of‑concept to production.
Maintain expertise in OpenAI's product suite and stay current on industry trends in generative AI, LLMs, and natural language processing.
Required Qualifications
3+ years in a Solutions Engineer, Sales Engineer, ML Engineer, or similar technical role.
Proficiency with Python, REST APIs, and common ML/AI libraries (e.g., Hugging Face Transformers, LangChain, OpenAI SDK).
Experience designing or deploying applications that utilize LLMs, embeddings, and RAG architecture.
Strong understanding of software architecture and integration patterns, especially within cloud environments (AWS, Azure, or GCP).
Excellent communication and stakeholder engagement skills, with the ability to explain complex topics to technical and non‑technical audiences.
Tools & Skills
OpenAI API (GPT‑4, GPT‑4o, DALL‑E, Whisper)
Prompt engineering, Retrieval‑Augmented Generation (RAG)
LangChain, LlamaIndex, vector databases (Pinecone, FAISS, Weaviate)
Python, FastAPI, front‑end integration
Knowledge of token limits, context management, cost optimization
Focus
Create custom GPT on a daily basis.
Specialize in using OpenAI's foundation models (e.g., GPT‑4, DALL‑E, Whisper).
Build applications and products powered by pre-trained LLMs rather than training models from scratch.
Typical Work
Use OpenAI APIs (chat, completion, embeddings, vision, audio) to build intelligent systems.
Design complex prompt workflows (prompt engineering, few‑shot learning, prompt chaining).
Integrate LLMs into apps for tasks like summarization, search, agents, chatbots, code generation, etc.
#J-18808-Ljbffr