Applied AI Engineer

Job Description

Job Description

Location: Houston, TX
Job Type: Full-Time
Experience: 3–5 Years
Salary: $125,000–$160,000 per year
Work Authorization: Must be legally authorized to work in the United States without current or future sponsorship.

Job Summary

We are seeking an Applied AI Engineer to design, develop, and deploy practical AI and machine learning solutions that address real business and operational needs. The ideal candidate will have hands-on experience with Python, machine learning, Generative AI, LLM applications, RAG, APIs, and cloud-based AI solutions .

This role will work closely with data, software, and business teams to turn AI concepts into reliable, scalable applications and automation workflows.

Responsibilities

• Design, develop, and deploy AI/ML and Generative AI solutions using Python and modern machine learning frameworks.
• Build and integrate LLM-powered applications, RAG pipelines, AI agents, and intelligent automation workflows .
• Develop data processing and model pipelines using Python, SQL, Pandas, NumPy, and Scikit-learn .
• Integrate AI applications with REST APIs, enterprise systems, databases, and external data sources .
• Develop prompt templates, evaluation workflows, retrieval strategies, and guardrails to improve LLM accuracy and reliability .
• Work with vector databases, embeddings, document processing, and semantic search for AI-enabled applications.
• Build and maintain production-ready AI services using FastAPI, Docker, Git, and cloud platforms .
• Evaluate model performance using appropriate metrics, test datasets, and real-world business scenarios.
• Collaborate with software engineers, data scientists, product teams, and business stakeholders to translate requirements into practical AI solutions.
• Monitor and troubleshoot deployed AI applications, addressing performance, data quality, reliability, and scalability issues.
• Maintain technical documentation covering AI workflows, model configurations, APIs, testing, and deployment processes.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, or a related technical field .
• 3–5 years of professional experience in AI/ML engineering, machine learning, data science, software engineering, or applied AI.
• Strong hands-on programming experience with Python .
• Experience with Machine Learning, Generative AI, LLMs, and AI application development .
• Working knowledge of RAG, embeddings, vector search, prompt engineering, and LLM evaluation .
• Strong SQL and data-processing skills.
• Experience developing and consuming REST APIs and working with JSON-based services.
• Experience with Git/version control, software development practices, and testing .
• Familiarity with Docker and cloud-based AI/ML environments .
• Strong analytical, problem-solving, communication, and collaboration skills.
• Must be legally authorized to work in the United States without current or future employer sponsorship.

Preferred Qualifications

• Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks .
• Experience with OpenAI, Azure OpenAI, Anthropic, Google Gemini, or other enterprise LLM platforms .
• Knowledge of AWS, Azure, or Google Cloud AI/ML services.
• Experience with Pinecone, FAISS, ChromaDB, pgvector, or other vector databases .
• Familiarity with MLOps, CI/CD, model deployment, monitoring, and AI evaluation frameworks .
• Experience with FastAPI, Kubernetes, or cloud-native application development .
• Understanding of responsible AI practices, data privacy, security, and access controls.
• Experience applying AI to enterprise workflows, automation, analytics, or operational processes.

What We Offer

• Competitive $125,000–$160,000 base salary
• Medical, dental, and vision benefits
• 401(k) with company contribution
• Paid time off and company holidays
• Professional development and learning opportunities
• Opportunity to work on Generative AI, machine learning, and enterprise AI applications
• Collaborative engineering and technology environment