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
