Ai Solution Architect

Job DescriptionJob Description

GenAI Solutions Architect

Role Overview: Join our AI ML team to drive AI advancements and enhance our products and services. You'll work with experts in AI ML modeling, ML engineering, data science, and data engineering.

Key Responsibilities:

• AI Architecture Strategy: Develop and implement AI architecture strategies, best practices, and standards.
• ML Architecture Design: Design and develop custom AI architectures for batch and stream processing-based AI ML pipelines.
• Collaboration: Work closely with data scientists, ML engineers, and software engineers to integrate ML models into production.
• Stakeholder Engagement: Collaborate with business and PM stakeholders to align technical milestones with business requirements.
• Infrastructure Design: Oversee the design of scalable and reliable AI, ML, GenAI, and LLM model training and deployment infrastructure.
• Model Deployment: Lead the deployment of GenAI, LLM, and ML models in production environments.
• Monitoring Systems: Design robust monitoring systems for model performance, data quality, and infrastructure.
• Security and Compliance: Implement security measures and compliance standards.
• Documentation: Maintain comprehensive documentation of AI processes and procedures.
• Standards and Best Practices: Ensure adherence to standards, governance, and best practices in AI pipeline and ML model monitoring.
• Problem Solving: Troubleshoot complex issues related to ML model deployments and data pipelines.
• Thought Leadership: Influence technical strategy and executive-level decisions.
• System Scaling: Build and scale production-ready AI systems for long-term business impact.
• Presentation Skills: Convey technical concepts to non-technical stakeholders.
• Adaptability: Communicate effectively with various audiences, from engineers to executive leadership.
• Passion for AI: Stay ahead of AI trends and leverage emerging technologies.
• Strategic Thinking: Demonstrate technical and business acumen and problem-solving skills.

Experience Required:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience as an ML engineer, architect, or lead data scientist in Big Data or cloud platforms.
• 4+ years of experience in ML architecture design and implementation for large-scale enterprise AI solutions.
• Proven success in collaborating with business, product, and PM stakeholders.
• Experience with Agile frameworks and delivery methods.
• Expertise in designing complex data-driven architectures for distributed computing and orchestration technology.
• Proficiency with public cloud platforms (AWS, GCP, Azure) and AI/ML technologies (Databricks, MLflow, Flink).
• Experience with SQL, NoSQL, ElasticSearch, MongoDB, Spark, Python, and PySpark.
• Knowledge of DevOps, MLOps principles, and CI/CD pipelines.
• Familiarity with trends in LLMs and open-source platforms.

This role is fully remote and will pay up to $250k per annum + bonus + benefits. If you feel you are suitable then please send your resume