• You build out the cloud and infrastructure for a production-grade platform • You introduce new cloud components for persistence, monitoring, and security • You establish a resilient operations foundation with logging, observability, and CI/CD pipelines • You provision cloud resources consistently and maintainably using Infrastructure as Code • You prepare technical foundations for robust artifact management and controlled audit access • You make well-founded technical decisions and surface risks early • You drive larger topics pragmatically into viable implementations

• Iteratively design and develop scalable, resilient, and efficient platform solutions using cloud services and modern software design frameworks. • Create modular, reusable infrastructure using Terraform and related tools. • Partner interdepartmentally and cross-functionally to strengthen DevOps practices through automation. • Architect, develop, and maintain CI/CD pipelines for platform functions and customer needs at scale. • Deliver solutions based on event-driven, object-oriented, and functional design patterns. • Own the design and implementation of monitoring and logging solutions to ensure reliability and performance. • Support the definition and maintenance of a lifecycle process for platform systems to ensure updates, patches, and security compliance. • Apply deep expertise in platform engineering while leveraging cross-disciplinary knowledge to drive effective collaboration across development, operations, and security teams. • Resolve cloud infrastructure issues quickly, analyze performance, and implement improvements. • Analyze system performance and implement optimizations to improve speed, efficiency, and resource utilization. • Anticipate and plan infrastructure scaling to meet the growing needs of the business. • Apply a security-first approach, ensuring SOC, SOC2, HIPAA, NIST, and regulatory requirements are met. • Implement and manage IAM, firewalls, and SIEM solutions. • Integrate diverse and non-traditional systems to deliver practical, forward-thinking outcomes. • Navigate challenges creatively and find effective solutions when conventional approaches fall short. • Lead assigned projects, driving cross-team collaboration, execution delivery, and accountability. • Write clean, efficient, and well-documented code while following best practices and established development standards. • Take part in the on-call rotation to ensure the reliability and availability of platform services. • Use generative AI tools such as Claude, Copilot, or ChatGPT to improve productivity and deliver high-quality outcomes.

• Design, build, and maintain scalable ML, AI, and data-platform services that power production features end-to-end. • Operate LLM applications in production: chat with memory, retrieval, prompt management, versioning, and experimentation. • Build and run structured evaluation pipelines (golden datasets, regression checks) so changes ship with confidence. • Own AI/ML observability and monitoring instrument, trace, and debug model behavior in prod with tools like Langfuse or MLflow (knowing one is enough). • Integrate and serve LLM-agnostic model backends (e.g., Anthropic models via Bedrock and Vertex) and support deterministic/custom ML where open-source models fall short (e.g., document/PDF parsing). • Contribute to data lineage, governance, and compliance as the platform matures. • Partner closely with product and the broader team to move fast without breaking quality.

• Design and enforce RBAC/ABAC policies, SCIM provisioning, and SSO/MFA for Databricks workspaces. • Manage identity lifecycle, including onboarding/offboarding and periodic access reviews. • Integrate Databricks and AWS services with enterprise IAM solutions (e.g., Azure AD, Okta). • Implement AWS IAM roles, policies, and permission boundaries for secure data access. • Ensure secure integration between AWS, Databricks, and Microsoft Power BI for reporting. • Develop and maintain security architecture for AWS and Databricks environments supporting Power BI analytics. • Design secure data pipelines and enforce encryption in transit and at rest across AWS S3, Databricks, and Power BI. • Implement network security controls (VPC, security groups, private endpoints) for AWS and Databricks connectivity. • Lead requirements gathering sessions with stakeholders to define security needs for AWS, Databricks, and Power BI integrations. • Document security requirements, architecture diagrams, and implementation plans. • Maintain detailed security design documentation and update as environments evolve. • Investigate and respond to IAM-related and platform security incidents and defects. • Ensure adherence to SOC 2, HIPAA, GDPR, and internal security standards across AWS and Databricks. • Implement data governance policies for sensitive data used in Power BI reporting. • Apply Databricks Security Profile features (CIS-hardened images, FIPS 140 encryption, TLS 1.2+). • Validate secure cluster configurations and enforce encryption policies in Databricks and AWS. • Harden AWS services (EC2, S3, IAM) following CIS benchmarks and best practices. • Partner with data engineering, BI, and cloud teams to implement security best practices. • Provide security posture reports and IAM metrics to leadership. • Support secure integration of Power BI with AWS and Databricks for enterprise reporting.