C the Signs

AI Engineer

• Architecting and Implementing Agentic Workflows
• Design Autonomous Loops: Build stateful control loops (Perception -> Reasoning -> Action) where agents can interpret clinical data, plan necessary checks, and generate risk assessments.
• Conversational Agentic workflow: Chatbot style user experience powered by LLM
• GCP Integration: Leverage Vertex AI for model serving and LLM models for reasoning, optimizing for long-context windows to process complex medical history.
• RAG & Grounding: Implement "Enterprise Grounding" using Vertex AI Vector Search to ensure all agent outputs are strictly cited against official medical literature (e.g., medical research and guidelines).
• Data & Tool Integration
• Structured Data Access: Build robust Python tools (Function Calling) that allow agents to securely query BigQuery or other datastores for patient demographics and symptoms.
• Security & Compliance: Ensure all AI operations comply with HIPAA/GDPR standards, implementing strict PII masking and data governance within the Google Cloud environment.
• System Reliability: Deploy agents on Vertex AI, Cloud Run, or GKE, ensuring low-latency inference and high availability for clinical users.
• Agent monitoring: implement effective product environment AI Agent execution monitoring and alert system to ensure SLA, safety and security compliance
• Leadership & Strategy
• Mentorship: Guide a team of engineers in MLOps best practices (CI/CD for models, evaluation pipelines).
• Evaluation: Implement "LLM-as-a-Judge" frameworks to automatically test agent accuracy against "Golden Datasets" of clinical cases.

Senior AI Developer – Agentic Healthcare Application

Product Designer

• Own the design vision for our consumer-facing platform across mobile and web
• Design flows that reduce friction and build trust as users share sensitive information, learn their cancer risk, and navigate next steps in a moment of high anxiety and uncertainty
• Translate complex risk assessment outputs and diagnostic pathways into clear, accessible user experiences
• Partner closely with C-suite, Product, Engineering, and Marketing teams to deliver cohesive experiences that align with our business strategy
• Conduct lightweight user research and testing to continuously validate and improve the experience
• Establish and evolve design systems, principles, and best practices
• Set the bar for design craft while balancing speed and quality in a fast-paced startup environment
• Lay the groundwork for building and mentoring a design team over time

Design Lead

Data Engineer

• Architect, build, and scale healthcare data platform
• Lead design and evolution of cloud-native data platform on GCP
• Build scalable ETL/ELT pipelines using dbt and Airflow
• Design and maintain BigQuery datasets and warehouse structures
• Implement data quality frameworks and ensure HIPAA compliance
• Partner with analytics and product teams to deliver data products
• Provide oversight and technical direction for multi-cloud integrations

Lead Data Engineer

Cloud Engineer

• Lead day-to-day monitoring and management of GCP infrastructure, focusing on reliability, uptime, security, performance, and compliance
• Manage GKE clusters, including cluster lifecycle, node pools, workload deployment, and operational best practices.
• Implement and maintain GCP networking: VPCs, firewall rules, service networking, and private connectivity.
• Support data and application teams using GCP services such as BigQuery, Cloud SQL, Pub/Sub, Cloud Storage, Cloud Run.
• Own and maintain Terraform configurations for GCP and AWS using reusable modules, remote state, policy checks, and automation pipelines.
• Automate environment provisioning, scaling, and configuration with CI/CD tools such as Cloud Build, GitHub Actions, ArgoCD, or Jenkins.
• Build tooling and workflows that improve developer productivity (automated builds, deployments, secrets management, ephemeral environments).
• Build and enhance observability stacks using Cloud Monitoring, Prometheus/Grafana, ELK/Elastic, or OpenTelemetry.
• Lead incident response, troubleshooting, RCA generation, and post-incident improvement efforts.
• Define and manage SLOs, error budgets, and operational runbooks.
• Ensure secure configurations across cloud services, Kubernetes workloads, secrets storage, and network boundaries.
• Implement guardrails and compliance automation using IAM best practices, GCP Organization Policies, and Terraform checks.
• Work with security and compliance teams to meet HIPAA, HITRUST, SOC 2, or internal audit requirements.
• Maintain stability of a pre-existing AWS environment by performing tasks such as:
• - Reviewing IAM roles and security posture
• - Supporting workloads on EC2, ECS, EKS, RDS, S3
• - Troubleshooting infrastructure or networking issues
• - Managing configurations, upgrades, and patching
• Assist teams that rely on AWS-hosted systems and ensure smooth integration with GCP-centric operations.
• Make small-to-medium improvements or automation updates for AWS infrastructure using Terraform or CI/CD workflows.
• Mentor DevOps, CloudOps, and Platform Engineers through pair programming, reviews, and best-practice sharing.
• Partner with development, data, and security teams to build highly reliable, cloud-native applications and pipelines.
• Establish operational standards, documentation, and playbooks for cloud operations.

Senior AI Developer – Agentic Healthcare Application

Design Lead

Lead Data Engineer

Lead CloudOps Engineer