Principal Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the complete design, development, and implementation of machine learning and Generative AI solutions.

• Influence architectural decisions across Databricks lakehouse platforms, as well as within AWS, GCP, and Azure ecosystems.

• Create and execute data pipelines for both batch and streaming data, develop data models, ML workflows, multi-agent architectures, and systems for autonomous decision-making.

• Construct and enhance scalable ETL/ELT pipelines using Databricks.

• Establish frameworks for evaluation, validation, governance, safety, and compliance concerning ML/GenAI systems.

• Collaborate with business stakeholders and product teams to convert objectives into quantifiable AI/ML solutions.

• Set best practices for MLOps, LLMOps, DataOps, and DevOps, including CI/CD, monitoring, observability, reproducibility, and cost-effective strategies.

• Design and manage scalable cloud-based data and AI platforms.

• Lead experimentation strategies, which include A/B testing and prompt optimization.

• Guide L4 and L5 engineers through design reviews, code assessments, and career mentoring.

• Foster collaboration among data engineering, data science, platform engineering, and business teams.

• Promote the adoption of innovations in data engineering and Generative AI/agentic systems.

⛳️ Requirements

• Doctorate degree with 2 years of experience, OR Master's degree with 4 years of experience, OR Bachelor's degree with 6 years of experience, OR Associate's degree with 10 years of experience, OR high school diploma/GED with 12 years of experience.

• Profound knowledge in machine learning, deep learning, and Generative AI.

• Proven experience in delivering production-grade ML/GenAI systems from start to finish.

• Proficient in MLOps/LLMOps ecosystems, including MLflow, Kubeflow, Airflow, CI/CD, Docker, and Kubernetes.

• Strong familiarity with AWS, Azure, or GCP and their cloud architecture principles.

• Experience with big data ecosystems, including Apache Spark, Hadoop, and distributed data processing.

• Expertise in building scalable data pipelines and platforms utilizing Databricks, Spark, SQL, and Python.

• Proficient in Python and contemporary ML/AI frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.

• Experience in designing evaluation and validation frameworks.

• Familiarity with RAG architectures, vector databases, and knowledge-grounded AI systems.

• Understanding of agentic AI frameworks, orchestration, planning, memory management, and tool integration.

• Solid foundation in statistical modeling, A/B testing, and causal inference.

• Experience with NLP, semantic search, embeddings, and vector search systems.

• Awareness of Responsible AI practices, including fairness, explainability, governance, and regulatory compliance.

• Experience with cloud-native AI/ML services and optimization of cost/performance.

• Familiarity with Databricks Lakehouse.

• Experience with red-teaming, adversarial testing, and synthetic data generation.

• Knowledge in OLAP and OLTP data modeling and performance tuning.

• Cloud certifications are advantageous.

🏝️ Benefits

• Retirement and Savings Plan featuring generous company contributions.

• Comprehensive group medical, dental, and vision coverage.

• Life and disability insurance options.

• Flexible spending accounts available.

• Discretionary annual bonus program.

• Stock-based long-term incentives.

• Award-winning time-off plans.

• Flexible work models where feasible.

• Opportunities for career development.

• Support for maintaining work/life balance.