Senior AI/ML Engineer

Job Title: Senior AI/ML Engineer
Location: Texas (Onsite/Hybrid)
Experience: 12+ Years

Job Summary

We are seeking a highly experienced AI/ML Engineer with 12+ years of IT experience and strong expertise in designing, developing, and deploying enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will have hands-on experience with Generative AI, Large Language Models (LLMs), MLOps, cloud platforms, and modern data engineering technologies.

Required Skills

• 12+ years of overall IT experience with at least 6+ years in AI/ML engineering.
• Strong programming skills in Python (mandatory).
• Expertise in Machine Learning, Deep Learning, NLP, and Computer Vision.
• Hands-on experience with Generative AI, Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), AI Agents, and prompt engineering.
• Experience with TensorFlow, PyTorch, Scikit-learn, Keras, Hugging Face Transformers, and LangChain/LlamaIndex.
• Strong knowledge of Vector Databases such as Pinecone, ChromaDB, FAISS, or Milvus.
• Experience with MLOps tools including MLflow, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.
• Experience deploying AI/ML solutions on AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
• Strong understanding of SQL, NoSQL databases, and data engineering concepts.
• Experience working with REST APIs, microservices, and distributed systems.
• Familiarity with Git, Azure DevOps, or GitHub Actions.
• Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications

• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLM platforms.
• Knowledge of AI governance, model monitoring, and responsible AI practices.
• Experience with Spark, Databricks, or distributed data processing.
• Exposure to multi-agent AI frameworks and autonomous AI systems.
• Relevant AI/ML or cloud certifications are preferred.

Responsibilities

• Design, develop, and deploy scalable AI/ML solutions for enterprise applications.
• Build and optimize Machine Learning and Deep Learning models for production environments.
• Develop Generative AI applications using LLMs, RAG pipelines, embeddings, and vector databases.
• Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions.
• Build robust MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Optimize model performance, scalability, accuracy, and inference latency.
• Implement secure and responsible AI practices, ensuring compliance with enterprise standards.
• Integrate AI services with cloud platforms and enterprise applications using APIs and microservices.
• Mentor junior engineers and provide technical leadership on AI initiatives.
• Stay updated with emerging AI technologies, frameworks, and industry best practices.

Education

• Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

Nice to Have

• Experience in Banking, Healthcare, Retail, Insurance, or Financial Services domains.
• Experience with Graph Neural Networks (GNNs), Reinforcement Learning, or Time Series Forecasting.
• Knowledge of Apache Spark, Kafka, Airflow, and Databricks.
• AI certifications from AWS, Microsoft Azure, Google Cloud, or NVIDIA.