Architect

Area(s) of responsibility

This role combines hands-on development, solution architecture, team mentorship, and operational ownership. The Tech Lead will own end-to-end delivery of GenAI platforms using Python, AWS Bedrock (Agent Core SDK), AWS Strands SDK, and modern DevOps and observability practices, ensuring scalability, security, reliability, and cost efficiency. Key Responsibilities Technical Leadership & Architecture

• Define and own end-to-end architecture for Generative AI applications deployed natively on AWS
• Lead technology decisions around: o AWS Bedrock models and agent design o Orchestration using AWS Strands SDK o Integration patterns (sync, async, event-driven)
• Establish standards for: o Prompt engineering o Agent workflows o Model lifecycle management Classification: Internal
• Review designs and code to ensure performance, scalability, and maintainability Generative AI Solution Delivery
• Lead hands-on development of: o GenAI services, agents, and APIs using Python o Bedrock Agent Core SDK–based applications
• Guide teams on: o Prompt optimization and guardrails o Cost-efficient token usage o Latency and throughput optimization
• Drive adoption of RAG, embeddings, and vector storage patterns where appropriate AWS-Native Cloud Engineering
• Design secure, scalable AWS architectures using: o AWS Lambda, ECS, EKS, EC2 o S3, DynamoDB, Aurora, OpenSearch o API Gateway / ALB
• Define IAM, networking, and security patterns aligned with Zero Trust and least privilege
• Ensure high availability, fault tolerance, and disaster recovery strategies DevOps, CI/CD & Platform Engineering
• Define and enforce CI/CD standards for GenAI workloads using: o AWS CodePipeline / CodeBuild / CodeDeploy o GitHub Actions / GitLab CI
• Lead Infrastructure-as-Code initiatives using: o AWS CDK / CloudFormation / Terraform Classification: Internal
• Automate testing, deployment, rollback, and environment promotion Observability, Reliability & Operations
• Own production observability strategy across AI and application layers: o CloudWatch logs, metrics, dashboards o AWS X-Ray distributed tracing o Custom metrics for AI behavior, latency, cost, and accuracy
• Define and monitor SLAs, SLOs, and error budgets
• Lead incident response, RCA, and continuous improvement Security, Governance & Responsible AI
• Ensure secure and compliant GenAI implementations: o Data encryption (at rest/in transit) o Secrets management o Secure prompt and data handling
• Define guardrails for: o Data privacy o Prompt injection risks o Model misuse and hallucinations
• Align AI implementations with enterprise governance and compliance frameworks Team Leadership & Stakeholder Management
• Mentor and guide developers and senior engineers
• Conduct design reviews, code reviews, and technical workshops
• Collaborate with: o Product managers Classification: Internal o Security and compliance teams o Platform and data engineering teams
• Translate business requirements into scalable technical solutions Required Skills & Qualifications Core Technical Skills (Must Have)
• Expert-level Python development
• Strong hands-on experience with: o AWS Bedrock o AWS Bedrock Agent Core SDK o AWS Strands SDK
• Deep expertise in AWS cloud-native architecture
• CI/CD, DevOps automation, and Infrastructure as Code
• Strong observability and production operations experience Preferred Skills