Job Title

Senior AI Architect / Principal AI Engineer (Python)

Experience

15+ Years Overall Experience in Software Engineering, Data Science, and Artificial Intelligence

Job Summary

We are seeking a highly experienced Senior AI Architect / Principal AI Engineer with 15+ years of industry experience to lead the design, development, and deployment of large-scale AI and Machine Learning solutions. The ideal candidate will have deep expertise in Python-based AI frameworks, strong architectural skills, and proven experience delivering production-grade AI systems across enterprise environments. This role requires technical leadership, hands-on development, and close collaboration with business and engineering stakeholders.

Key Responsibilities

Architect, design, and implement end-to-end AI/ML solutions using Python
Lead development of Machine Learning, Deep Learning, and Generative AI models
Define AI architecture standards, best practices, and governance
Build scalable data pipelines, model training, validation, and deployment workflows
Oversee model lifecycle management (MLOps) including monitoring and retraining
Guide teams on model performance, explainability, fairness, and ethical AI
Collaborate with product owners, data engineers, cloud teams, and executives
Review code, mentor senior and junior engineers, and drive technical excellence
Translate business problems into AI-driven solutions with measurable impact
Stay current with emerging AI technologies and industry trends

Required Technical Skills

Programming & Core Technologies

Expert-level Python (15+ years)
Strong proficiency in OOP, Design Patterns, and Clean Code practices
Experience with REST APIs, Microservices, and Event-driven architectures

AI / Machine Learning

Machine Learning: Scikit-learn, XGBoost, LightGBM
Deep Learning: TensorFlow, Keras, PyTorch
Generative AI & LLMs: OpenAI, Hugging Face, LangChain, Llama, RAG architectures
Natural Language Processing (NLP), Computer Vision (CV), Time Series Analysis
Model evaluation, optimization, and hyperparameter tuning

Data Engineering & Analytics

Data processing: Pandas, NumPy, Dask, Spark
Databases: SQL, NoSQL (MongoDB, Cassandra)
Data Warehousing & Lakes: Snowflake, BigQuery, Redshift, Delta Lake

MLOps & DevOps

Model deployment: Docker, Kubernetes
MLOps tools: MLflow, Kubeflow, Airflow
CI/CD pipelines and automated testing for ML systems
Model monitoring, drift detection, and retraining strategies

Cloud Platforms

AWS / Azure / GCP (at least one at expert level)
AI services: SageMaker, Azure ML, Vertex AI
Scalable and secure cloud-based AI solutions

Leadership & Soft Skills

Proven experience as Technical Lead / Architect
Strong communication and stakeholder management skills
Ability to mentor, coach, and grow high-performing AI teams
Experience working with global and cross-functional teams
Strong problem-solving and decision-making skills

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