AI Application Engineer

Role: AI Application Engineer

Location: Santa Clara, CA (Hybrid)

Type: Contract

Overview:

AI Application Engineer to support the development and delivery of next-generation AI-powered applications built on NVIDIA infrastructure. This role will focus on production-grade LLM application engineering, RAG quality, prompt engineering, AI safety, and orchestration of complex multi-step AI pipelines.

Day-to-Day Responsibilities

• Design, develop, and optimize production-grade LLM-powered applications
• Own AI quality, RAG accuracy, prompt engineering, and AI safety across multiple applications
• Develop and maintain multi-step LLM orchestration pipelines using LangChain, LlamaIndex, or custom frameworks
• Implement and optimize RAG pipelines including chunking strategies, embedding selection, reranking, and hybrid search
• Design multi-turn conversational AI experiences with context management and session memory
• Integrate NVIDIA technologies including NIM, NeMo, NeMoGuardrails, and Riva into enterprise AI applications
• Build automated evaluation pipelines for model quality, hallucination detection, regression testing, and release gating
• Perform latency profiling and optimization across multi-step LLM call chains
• Implement AI safety guardrails including prompt injection prevention, jailbreak mitigation, and topical control
• Collaborate with globally distributed engineering and product teams to deliver scalable AI solutions
• Support deployment, monitoring, and continuous improvement of AI applications in production environments

Basic Qualifications:

• 4–7 years of software engineering experience with at least 2 years focused on production LLM application development
• Expert-level experience with Python for AI/ML application development and async programming
• Strong expertise in prompt engineering including system prompts, few-shot prompting, and instruction tuning
• 3+ Years of Hands-on experience with multi-step LLM orchestration frameworks such as LangChain or LlamaIndex
• 3+ Years of Experience designing and optimizing RAG pipelines and retrieval systems
• 3+ Years of Experience with vector databases, similarity search tuning, and reranking techniques
• 3+ Years of Hands-on experience with NVIDIA NIM, NeMo, NeMoGuardrails, and Riva
• 3+ Years of Experience implementing AI safety and guardrails for customer-facing applications
• Strong knowledge of automated AI evaluation frameworks such as RAGAS or TruLens
• 3+ Years of Experience profiling and optimizing latency in multi-step AI pipelines
• Ability to work onsite in Santa Clara, CA
• Preferred Qualifications
• Experience with adaptive learning systems or recommendation engines
• Knowledge graph integration experience with RAG architectures
• Experience with multi-agent orchestration patterns
• ServiceNow API integration experience
• Prior experience building AI products on NVIDIA infrastructure
• Experience with streaming LLM response handling and real-time AI applications

Technology Stack

• Python
• LangChain
• LlamaIndex
• NVIDIA NIM
• NeMo
• NeMoGuardrails
• NVIDIA Riva
• Vector Databases
• RAGAS / TruLens
• LLM APIs and orchestration frameworks

Education

• Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, or equivalent work experience.