AI Engineer

Job Description

Our client operates at the crossroads of energy and home services, fueled by the vision of a smarter, cleaner future. Committed to developing groundbreaking solutions, they aim to streamline their customers’ lives by providing energy, protection, and smart services for their homes and businesses.

Our client is 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 (GCP) 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 GCP 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.