Overview
Skills
Job Details
AI Engineer requirement details.
Location: Houston, TX hybrid 3 days per week onsite
Job Title: Applied AI Engineer
Job Summary:
We are seeking a talented and driven Applied AI Engineer to join our growing Data & AI team. This role is ideal for an experienced software engineer with a deep understanding of generative AI technologies and a passion for building scalable, production-grade AI solutions. You will be responsible for designing, prototyping, and deploying GenAI-powered applications, while also contributing to our AI platform architecture across cloud environments such as Google Cloud Platform (Google Cloud Platform) and Microsoft Azure.
Key Responsibilities:
- Translate business needs into robust, scalable GenAI technical solutions.
- Design, prototype, and implement LLM-driven applications using techniques such as RAG, prompt engineering, fine-tuning, and vector search.
- Develop APIs and reusable software components in Python to support GenAI applications.
- Leverage orchestration frameworks (e.g., LangChain, LlamaIndex, or LangGraph) to deliver dynamic and modular AI workflows.
- Collaborate with cross-functional teams to integrate AI capabilities into business applications.
- Deploy and monitor GenAI models and pipelines using cloud-native tools, Kubernetes, and serverless architectures.
- Continuously evaluate model and system performance, implementing improvements as needed.
- Create and maintain technical documentation and support materials for deployed solutions.
Working Conditions:
- Hybrid work model: Onsite in Houston office 3 days per week.
- Open office environment.
Minimum Requirements:
- Bachelor s or Master s degree in Computer Science, AI/ML, or a related field.
- 5+ years of software development experience with strong Python skills.
- 2 3+ years of hands-on experience building GenAI/LLM-based applications.
- Experience developing multi-step agent workflows using LangGraph or similar orchestration frameworks.
- Proficient in designing retrieval pipelines: document loaders, chunking strategies, embedding models, and vector database integration.
- Strong grasp of GenAI concepts, including:
- Retrieval-Augmented Generation (RAG)
- Embeddings & vector databases (e.g., FAISS, Pinecone, ChromaDB)
- Prompt engineering and fine-tuning
- LLM APIs (e.g., OpenAI, Claude, Gemini)
- Experience deploying cloud-native solutions using Google Cloud Platform and/or Azure.
- Solid understanding of API design, microservices, and software architecture patterns.
- Familiarity with version control systems (e.g., Git, Azure DevOps).
- Experience with Docker and Kubernetes.
- Demonstrated ability to build and scale AI/ML solutions from proof-of-concept to production.
Preferred Qualifications:
- Experience with GenAI orchestration tools (e.g., LangChain, LlamaIndex).
- Familiarity with DevOps practices: Azure DevOps, YAML pipelines, Terraform.
- Strong interpersonal and communication skills, with the ability to collaborate across teams and influence decision-making.
- Self-starter with a proactive mindset and strong problem-solving abilities.
- Ability to work both independently and in collaborative team environments.
- Interest in leveraging AI tools to enhance productivity and solution delivery.