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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Python AI/ML Engineer - **Company:** Kforce Inc. - **Location:** Coppell, TX, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Application Frameworks, Build Automation, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Software Quality, Continuous Integration, Information Engineering, Software Debugging, DevOps, Github, Python (Programming Language), Machine Learning, Performance Tuning, Cloud Services, Tensorflow, Software Engineering, SQL Databases, Systems Integration, Unstructured Data, Google Cloud, Enterprise Software Applications, Performance Testing, Feature Engineering, Data Ingestion, Spring Cloud, Pytorch, LangChain, Bitbucket Pipelines, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Model Validation, Llamaindex, Generative AI, Backend, Git, Fastapi, Pyspark, Scikit Learn, Kubernetes, Information Technology, Production Code, Machine Learning Operations, Drift Detection, Restful APIs, Semantic Kernel, Software Version Control, Data Pipelines, Docker, Jenkins, Databricks, Vulnerability Analysis, Microservices - **Published:** October 15, 2026 - **Apply:** https://www.dice.com/job-detail/b96d0a49-2e00-4014-bab4-564a5fd49126 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent professional experience * 8-12 years of software engineering experience, including substantial hands-on Python development * Production experience designing, deploying, and supporting AI/ML solutions * Strong understanding of machine learning algorithms, model lifecycle management, and MLOps principles * Experience developing RESTful APIs, microservices, and system integrations * Hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform * Demonstrated experience creating and maintaining CI/CD pipelines and applying DevOps practices * Experience with Docker, Kubernetes, SQL, Git, automated testing, debugging, and production support * Strong analytical, communication, stakeholder-management, and problem-solving skills, * Experience with Generative AI, large language models, prompt engineering, RAG, embeddings, and vector databases * Hands-on knowledge of frameworks such as LangChain, LlamaIndex, Semantic Kernel, scikit-learn, TensorFlow, or PyTorch * Experience with Snowflake, Databricks, Spark, PySpark, MLflow, Kubeflow, or Airflow * Experience building cloud-native applications using FastAPI or Flask * Experience in financial services, audit, risk, compliance, or another highly regulated enterprise environment * Knowledge of responsible AI, model governance, data privacy, security, and enterprise control requirements ## Description Kforce has a client that is seeking a Senior Python AI/ML Engineer in Coppell, TX. Duties Include: * Design, develop, test, and deploy machine learning and Generative AI solutions for enterprise use cases * Build and optimize end-to-end AI/ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring * Develop Retrieval-Augmented Generation (RAG) solutions and integrate large language models into enterprise applications * Perform model evaluation, performance tuning, prompt optimization, and ongoing solution improvement Python and API Engineering: * Develop scalable backend services, microservices, and RESTful APIs using Python * Create reusable frameworks, libraries, and integration components * Write clean, secure, maintainable, and production-quality code using modern engineering standards * Implement unit, integration, regression, and performance testing Data Engineering and Integration: * Design data pipelines for structured and unstructured data processing * Integrate AI/ML models with internal and external enterprise systems through APIs and event-driven patterns * Work with cloud data platforms such as Snowflake, Databricks, or comparable technologies * Collaborate with data engineering teams to support data quality, lineage, governance, and security requirements MLOps, DevOps and CI/CD: * Build and maintain CI/CD pipelines for application, infrastructure, and model deployments * Automate build, test, code-quality checks, security scanning, deployment, and release processes * Implement MLOps practices including model versioning, experiment tracking, monitoring, drift detection, and retraining * Use tools such as Jenkins, GitHub Actions, Azure DevOps, Bitbucket Pipelines, Docker, and Kubernetes Cloud Engineering: * Design and deploy cloud-native solutions using AWS, Azure, or Google Cloud Platform