J
Gen AI Engineer
Jade Business Services (JBS)
2 hours ago
Full-time
On-site
Houston, Texas, United States
We are looking for a skilled
AI Engineer - Generative AI / LLM
with 3-7 years of experience in designing and developing AI-powered applications. The ideal candidate should have strong hands-on experience with
Generative AI, Large Language Models (LLMs), RAG, prompt engineering, and Python .
The candidate will work on building scalable AI solutions using modern LLM frameworks and cloud technologies, integrating AI capabilities into enterprise applications and business workflows.
Key Responsibilities
Design, develop, and deploy
Generative AI and LLM-powered applications .
Build production-ready solutions using
RAG (Retrieval-Augmented Generation)
and knowledge-based AI systems.
Work with LLMs such as
OpenAI GPT, Azure OpenAI, Claude, Gemini, Llama , or similar models.
Develop AI workflows using frameworks such as
LangChain, LlamaIndex, LangGraph , or equivalent.
Implement
prompt engineering , prompt optimization, structured outputs, and function/tool calling.
Develop and integrate
vector databases
such as Pinecone, Azure AI Search, Weaviate, Chroma, Milvus, or FAISS.
Build document ingestion and processing pipelines for PDFs, documents, web content, and enterprise data.
Implement techniques such as
embeddings, semantic search, chunking, metadata filtering, and reranking .
Develop APIs and backend services using
Python, FastAPI, Flask, or Django .
Integrate LLM solutions with enterprise applications, databases, APIs, and cloud services.
Evaluate LLM performance using appropriate
accuracy, relevance, hallucination, latency, and cost metrics .
Implement responsible AI practices including security, data privacy, access control, and guardrails.
Optimize AI applications for scalability, performance, reliability, and cost.
Collaborate with data scientists, software engineers, architects, product teams, and business stakeholders.
Troubleshoot and continuously improve AI models and applications based on production feedback.
Required Skills
3-7 years of software/AI engineering experience .
Strong programming experience in
Python .
Hands-on experience building
Generative AI / LLM applications .
Strong understanding of
LLMs, Transformers, embeddings, prompt engineering, and NLP concepts .
Hands-on experience with
RAG architecture .
Experience with at least one LLM framework such as:
LangChain
LangGraph
Semantic Kernel
Experience with one or more
Vector Databases/Search technologies :
Pinecone
FAISS
Chroma
Weaviate
Milvus
Experience working with LLM providers such as
OpenAI/Azure OpenAI, Anthropic, Google Gemini, AWS Bedrock, or open-source LLMs .
Good understanding of
SQL and databases .
Experience with
Git, CI/CD, Docker , and software development best practices.
Strong understanding of
API integration, authentication, logging, monitoring, and debugging .
Preferred / Nice-to-Have Skills
Experience with
AWS, Azure, or GCP .
Experience with
Kubernetes
and containerized AI applications.
#J-18808-Ljbffr
AI Engineer - Generative AI / LLM
with 3-7 years of experience in designing and developing AI-powered applications. The ideal candidate should have strong hands-on experience with
Generative AI, Large Language Models (LLMs), RAG, prompt engineering, and Python .
The candidate will work on building scalable AI solutions using modern LLM frameworks and cloud technologies, integrating AI capabilities into enterprise applications and business workflows.
Key Responsibilities
Design, develop, and deploy
Generative AI and LLM-powered applications .
Build production-ready solutions using
RAG (Retrieval-Augmented Generation)
and knowledge-based AI systems.
Work with LLMs such as
OpenAI GPT, Azure OpenAI, Claude, Gemini, Llama , or similar models.
Develop AI workflows using frameworks such as
LangChain, LlamaIndex, LangGraph , or equivalent.
Implement
prompt engineering , prompt optimization, structured outputs, and function/tool calling.
Develop and integrate
vector databases
such as Pinecone, Azure AI Search, Weaviate, Chroma, Milvus, or FAISS.
Build document ingestion and processing pipelines for PDFs, documents, web content, and enterprise data.
Implement techniques such as
embeddings, semantic search, chunking, metadata filtering, and reranking .
Develop APIs and backend services using
Python, FastAPI, Flask, or Django .
Integrate LLM solutions with enterprise applications, databases, APIs, and cloud services.
Evaluate LLM performance using appropriate
accuracy, relevance, hallucination, latency, and cost metrics .
Implement responsible AI practices including security, data privacy, access control, and guardrails.
Optimize AI applications for scalability, performance, reliability, and cost.
Collaborate with data scientists, software engineers, architects, product teams, and business stakeholders.
Troubleshoot and continuously improve AI models and applications based on production feedback.
Required Skills
3-7 years of software/AI engineering experience .
Strong programming experience in
Python .
Hands-on experience building
Generative AI / LLM applications .
Strong understanding of
LLMs, Transformers, embeddings, prompt engineering, and NLP concepts .
Hands-on experience with
RAG architecture .
Experience with at least one LLM framework such as:
LangChain
LangGraph
Semantic Kernel
Experience with one or more
Vector Databases/Search technologies :
Pinecone
FAISS
Chroma
Weaviate
Milvus
Experience working with LLM providers such as
OpenAI/Azure OpenAI, Anthropic, Google Gemini, AWS Bedrock, or open-source LLMs .
Good understanding of
SQL and databases .
Experience with
Git, CI/CD, Docker , and software development best practices.
Strong understanding of
API integration, authentication, logging, monitoring, and debugging .
Preferred / Nice-to-Have Skills
Experience with
AWS, Azure, or GCP .
Experience with
Kubernetes
and containerized AI applications.
#J-18808-Ljbffr