Systems Architect

4 weeks ago

Washington, United States TalTeam Full time
Title: Systems Architect - Cloud and AI Solutions
Technical Skill Set:
  1. Cloud Architecture :
    • Extensive experience designing and deploying cloud-based solutions using AWS, Azure, or GCP.
    • Expertise in cloud-native technologies, including serverless architecture (AWS Lambda, Azure Functions) and container orchestration (Kubernetes, Docker).
    • Knowledge of hybrid and multi-cloud strategies to ensure system flexibility and redundancy.
  2. Security and Compliance :
    • Proficient in implementing FedRAMP Moderate/High and NIST SP 800-53 security controls.
    • Expertise in access control systems (e.g., RBAC, ABAC) and authentication protocols (e.g., OAuth2, SAML).
    • Skilled in securing data in transit and at rest using encryption protocols (e.g., AES-256, TLS 1.3).
  3. SaaS Platform Design :
    • Experience building scalable, multi-tenant SaaS platforms with high availability (99.5% uptime).
    • Proficient in integrating API-driven architectures and ensuring seamless interoperability with existing systems.
    • Skilled in implementing logging and monitoring solutions for SaaS platforms using tools like Splunk, CloudWatch, or Azure Monitor.
  4. I/ML Integration :
    • Strong knowledge of integrating AI/ML solutions into existing workflows.
    • Experience designing data pipelines for deploying machine learning models (e.g., TensorFlow Serving, TorchServe).
    • Familiarity with edge computing for deploying AI models closer to data sources.
  5. Networking and Infrastructure :
    • Deep understanding of networking concepts, including VPNs, firewalls, and load balancers.
    • Experience with software-defined networking (SDN) and virtual private clouds (VPCs).
    • Skilled in optimizing network performance for SaaS platforms.
  6. Data Management :
    • Expertise in designing scalable databases (SQL and NoSQL) for structured and unstructured data.
    • Knowledge of big data technologies like Apache Hadoop, Spark, and AWS Redshift.
    • Experience with ETL/ELT workflows to process and transform data for AI/ML applications.
  7. Disaster Recovery and High Availability :
    • Proficient in designing failover mechanisms and disaster recovery plans for mission-critical systems.
    • Experience with tools like AWS Elastic Disaster Recovery, Azure Site Recovery, and GCP Backup and DR.
  8. Microservices and API Design :
    • Hands-on experience with microservices architecture, using frameworks like Spring Boot or Node.js.
    • Expertise in designing RESTful APIs and implementing API gateways (e.g., AWS API Gateway, Kong).
  9. Performance Optimization :
    • Skilled in designing systems to handle large-scale workloads using auto-scaling and load balancing techniques.
    • Proficient in optimizing database queries, storage solutions, and compute resources for cost-efficiency.
  10. Collaboration and Leadership :
    • bility to lead cross-functional teams, including developers, analysts, and cybersecurity experts.
    • Skilled in documenting architecture designs using tools like Visio, Lucidchart, or Draw.io.
    • Experience working closely with stakeholders to translate business requirements into technical specifications.

Tools and Technologies:
  1. Cloud Platforms :
    • WS (SageMaker, EC2, S3, RDS, CloudFront)
    • zure (Azure ML, Blob Storage, Virtual Machines, Cognitive Services)
    • GCP (Vertex AI, BigQuery, Cloud Functions)
  2. I/ML Frameworks :
    • TensorFlow, PyTorch, Scikit-learn
    • Hugging Face Transformers for model integration
  3. Monitoring and Logging :
    • Splunk, Datadog, AWS CloudWatch, Azure Monitor
  4. Networking and Security :
    • OpenVPN, Palo Alto firewalls, Zero Trust Architectures
  5. DevOps and CI/CD :
    • Jenkins, GitHub Actions, Terraform, Ansible
  6. Databases :
    • SQL: PostgreSQL, MySQL, Oracle
    • NoSQL: MongoDB, DynamoDB, Cassandr

Responsibilities in Project Context:
  1. Designing the SaaS Platform :
    • Create a FedRAMP-compliant cloud-based architecture tailored for the client's AI initiatives.
    • Ensure scalability, reliability, and security of the platform to meet 24/7 operational requirements.
  2. Integrating AI Solutions :
    • Collaborate with data scientists to deploy and manage AI models in a production environment.
    • Implement robust data pipelines to support AI workflows, ensuring high-performance processing of large datasets.
  3. Compliance and Security :
    • Develop and maintain security frameworks aligned with FedRAMP and NIST standards.
    • Monitor system vulnerabilities and ensure incident response readiness.
  4. Collaboration with Teams :
    • Work closely with program managers, senior developers, and cybersecurity analysts to align technical designs with business goals.
    • Provide mentorship and guidance to development teams on best practices for cloud and SaaS architecture.


**Talteam Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.**

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