Senior Python AI/ML Engineer

Key Responsibilities

• Design, develop, test, and deploy AI/ML and Generative AI solutions for enterprise applications.
• Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop RAG solutions and integrate large language models into enterprise systems.
• Build scalable Python applications, backend services, microservices, and RESTful APIs.
• Design data pipelines and integrate structured and unstructured data across enterprise platforms.
• Implement CI/CD pipelines, automated testing, and secure deployment workflows.
• Apply MLOps practices, including model versioning, experiment tracking, monitoring, drift detection, and retraining.
• Deploy cloud-native applications using AWS, Azure, or GCP, with Docker and Kubernetes.
• Collaborate with data engineering, platform, and business teams to ensure solution quality, security, scalability, and reliability.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience.
• 8–12 years of software engineering experience, including substantial hands-on Python development.
• Production experience developing and deploying AI/ML solutions.
• Strong understanding of machine learning algorithms, model evaluation, and MLOps principles.
• Experience building RESTful APIs, microservices, and enterprise integrations.
• Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience with CI/CD pipelines, DevOps practices, Docker, Kubernetes, SQL, Git, and automated testing.
• Strong debugging, analytical, communication, and problem-solving skills.

Preferred Qualifications

• Experience with Generative AI, LLMs, RAG, prompt engineering, embeddings, and vector databases.
• Familiarity with LangChain, LlamaIndex, Semantic Kernel, scikit-learn, TensorFlow, or PyTorch.
• Experience with Snowflake, Databricks, Spark, PySpark, MLflow, Kubeflow, or Airflow.
• Experience developing APIs using FastAPI or Flask.
• Knowledge of responsible AI, model governance, data privacy, and enterprise security requirements.
• Experience in financial services or other regulated enterprise environments.

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