Aptino, Inc.
GenAI Design Architect (Santa Clara County)
Aptino, Inc., Santa Clara, California, United States
Role:
GenAI Design Architect Location:
Santa Clara County, California, United States (Onsite) Duration:
12 months
We are looking for a skilled
AI Architect
with strong expertise in
OpenAI technologies, Python development, and building AI-driven applications . The ideal candidate should have hands-on experience in designing, developing, and deploying LLM-based solutions, integrating OpenAI APIs, and working with machine learning pipelines.
Key Responsibilities Design, develop, and implement AI/LLM-based solutions using
OpenAI models (GPT, Embeddings, Assistants, Vector Stores, Fine-tuning) . We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI-powered solutions. Build robust, scalable
Python applications
integrating OpenAI APIs and other GenAI frameworks. Develop end-to-end pipelines for
prompt engineering, data preprocessing, model evaluation, and deployment . Collaborate with product and engineering teams to identify AI use cases and deliver production-ready solutions. Optimize model performance, latency, and cost using best practices. Create tools, scripts, and automations for AI workflows (e.g., embeddings, RAG systems, chatbots). Ensure AI systems follow security, compliance, and ethical guidelines. Maintain documentation, architecture diagrams, and code quality standards. Required Skills & Qualifications Bachelors or Masters degree in Computer Science, Engineering, AI/ML, or related field. 26 years
of experience as an AI Engineer / ML Engineer / Python Developer. Strong programming proficiency in
Python
and related libraries (FastAPI, Flask, Pandas, NumPy). Hands-on experience with
OpenAI APIs , including GPT models, Assistants, Function Calling, Fine-tuning, and Embeddings. Experience building
LLM-based applications , such as chatbots, RAG systems, classification tools, automation agents, or content generation engines. Familiarity with vector databases (Pinecone, ChromaDB, FAISS, Weaviate). Knowledge of cloud platforms ( AWS, Azure, GCP ) and containerization (Docker). Understanding of ML fundamentals: NLP, model evaluation, prompt engineering. Strong problem-solving, analytical, and communication skills.
GenAI Design Architect Location:
Santa Clara County, California, United States (Onsite) Duration:
12 months
We are looking for a skilled
AI Architect
with strong expertise in
OpenAI technologies, Python development, and building AI-driven applications . The ideal candidate should have hands-on experience in designing, developing, and deploying LLM-based solutions, integrating OpenAI APIs, and working with machine learning pipelines.
Key Responsibilities Design, develop, and implement AI/LLM-based solutions using
OpenAI models (GPT, Embeddings, Assistants, Vector Stores, Fine-tuning) . We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI-powered solutions. Build robust, scalable
Python applications
integrating OpenAI APIs and other GenAI frameworks. Develop end-to-end pipelines for
prompt engineering, data preprocessing, model evaluation, and deployment . Collaborate with product and engineering teams to identify AI use cases and deliver production-ready solutions. Optimize model performance, latency, and cost using best practices. Create tools, scripts, and automations for AI workflows (e.g., embeddings, RAG systems, chatbots). Ensure AI systems follow security, compliance, and ethical guidelines. Maintain documentation, architecture diagrams, and code quality standards. Required Skills & Qualifications Bachelors or Masters degree in Computer Science, Engineering, AI/ML, or related field. 26 years
of experience as an AI Engineer / ML Engineer / Python Developer. Strong programming proficiency in
Python
and related libraries (FastAPI, Flask, Pandas, NumPy). Hands-on experience with
OpenAI APIs , including GPT models, Assistants, Function Calling, Fine-tuning, and Embeddings. Experience building
LLM-based applications , such as chatbots, RAG systems, classification tools, automation agents, or content generation engines. Familiarity with vector databases (Pinecone, ChromaDB, FAISS, Weaviate). Knowledge of cloud platforms ( AWS, Azure, GCP ) and containerization (Docker). Understanding of ML fundamentals: NLP, model evaluation, prompt engineering. Strong problem-solving, analytical, and communication skills.