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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Solutions Architect - MySQL - **Company:** HCL America Inc. - **Location:** Durham, NC, United States - **Experience:** Experienced - **Salary:** $172,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Relational Databases, Distributed Computing Environment, Electronic Data Interchange (EDI), Github, Graph Database, Python (Programming Language), PostgreSQL, Machine Learning, Meta-Data Management, MySQL, Natural Language Processing, Neo4j, NumPy, Cloud Services, Tensorflow, SQL Databases, Systems Integration, Management of Software Versions, Datadog, Feature Engineering, Pytorch, Delivery Pipeline, Large Language Models, Snowflake, Grafana, Apache Spark, Deep Learning, Fastapi, Pandas, Data Lakes, Pyspark, Scikit Learn, Kubernetes, Data Lineage, HuggingFace, Xgboost, Apache Kafka, Spark Streaming, Data Management, Machine Learning Operations, Cloudwatch, Restful APIs, Terraform, Data Pipelines, Cisco, Docker, Databricks - **Published:** August 9, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a67ae1ade25d4115 ## About the Role * 15+ years of hands-on data engineering and architecture experience, with 3-5+ years building production AI/ML and LLM-era data infrastructure. * Proven experience designing enterprise-scale AI data platforms that serve multiple AI consumers -not just one application or pipeline. * Deep expertise in lakehouse and data mesh architectures: Databricks, Delta Lake, PySpark, Kafka, Spark Structured Streaming, cloud-native data services (AWS, Azure). * Hands-on experience with vector stores, semantic models, knowledge graphs, and retrieval infrastructure in production environments. * Working knowledge of LLMOps: model serving pipelines, MLflow, CI/CD for AI, automated evaluation, and production monitoring. * Strong background in data governance, security, and compliance in regulated industries (financial services, payments, cybersecurity, healthcare). * Experience defining data access controls for AI agents and automated systems - not just, 1. Expert Proficiency In Ai/Ml Model Development Using Python, Tensorflow, Pytorch, And Scikitlearn. 2. Excellent Knowledge Of Distributed Data Processing With Apache Spark And Kafka. 3. Advanced Skills In Data Engineering, Feature Extraction, And Pipeline Automation Using Pandas, Numpy, And Apache Airflow. 4. Solid Understanding Of Classical Machine Learning, Deep Learning, Nlp, And Time Series Forecasting Techniques. 5. Indepth Experience With Relational Databases Such As Mysql And Postgresql For Data Management And Model Storage. 6. Strong Ability To Architect Scalable Solutions Integrating Multiple Data Sources And Ml Frameworks. 7. Excellent Communication And Mentoring Skills To Guide Technical Teams. Skills: * Expert: Python, SQL, PySpark, Kafka, Databricks, Delta Lake, Snowflake,AWS (S3, Glue, EKS, Bedrock, Kinesis, Redshift), Docker, Kubernetes, Terraform, GitHub Actions. * Strong: LangChain, LlamaIndex, LLM APIs (OpenAI, AWS Bedrock, Claude, HuggingFace), vector databases (Pinecone, FAISS, ChromaDB, OpenSearch), knowledge graphs (Neo4j). Cisco Confidential * Solid: MLflow, FastAPI, CI/CD pipelines, observability tooling (CloudWatch, Grafana, or equivalent), data lineage and metadata management platforms. Other Requirements 1. Recommended: TensorFlow Developer Certificate 2. AWS Certified Machine Learning � Specialty 3. Databricks Certified Data Engineer Professional (optional but valuable) ## Description This role is responsible for architecting and designing advanced AI/ML solutions that leverage modern data platforms and machine learning frameworks. The individual will drive technical strategy, oversee solution delivery, and ensure alignment with business objectives by integrating scalable machine learning models and robust data pipelines. They will provide expert guidance to the team, foster innovation, and champion best practices in AI/ML engineering., 1. Architect end-to-end AI/ML solutions using Python, TensorFlow, PyTorch, and scikit-learn, ensuring scalable model deployment and integration with enterprise systems. 2. Design and implement distributed data processing workflows with Apache Spark and Kafka to support real-time and batch ML model operations. 3. Develop robust data pipelines and feature engineering processes using pandas, NumPy, and Apache Airflow to optimize model performance and data quality. 4. Oversee the development and validation of machine learning models for NLP, deep learning, and time series forecasting, applying advanced techniques and frameworks such as XGBoost and LightGBM. 5. Define and enforce architectural standards for model storage, versioning, and reproducibility using MySQL, PostgreSQL, and DataBricks. 6. Mentor team members on AI/ML best practices and emerging technologies, ensuring continuous skill enhancement and technical excellence. 7. Collaborate with internal stakeholders to gather requirements and translate business needs into technical specifications for AI/ML solutions. 8. Evaluate and integrate new tools and technologies to maintain solution relevance and meet evolving client requirements. 9. 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