AWS AI Senior Tech Lead

Job Title:- AWS AI Senior Tech Lead
Location:- Jersey City NJ (Onsite)
Job Type: Full Time
Salary Range: $120000 to $150000/Annum Full Time Benefits


Must Have Technical/Functional Skills
AWS Certified Solutions Architect Professional or equivalent cloud architecture certification preferred.
Strong hands-on capability in Python TypeScript/JavaScript REST APIs microservices event-driven patterns and containerized deployments.
Experience with AWS Bedrock SageMaker Lambda Step Functions ECS/EKS API Gateway S3 CloudWatch and CI/CD tooling.
Deep understanding of prompt engineering agent orchestration tool integration vector stores embeddings model evaluation and AI guardrails.
Ability to enforce engineering standards code quality secure coding performance tuning and observability practices.
Strong leadership mentoring estimation planning and stakeholder communication skills.
Familiarity with compliance audit logging model risk controls and responsible AI practices
Strong understanding of AI agent patterns prompt orchestration tool/function calling RAG pipelines model evaluation guardrails and observability.
Strong application security and cloud security knowledge including threat modeling OWASP/API security identity and access management encryption secure SDLC logging monitoring and resilience patterns.
Ability to define non-functional requirements for security privacy performance resiliency scalability auditability and operational readiness.
Excellent communication skills with ability to present architecture decisions risks and trade-offs to senior stakeholders.

Roles & Responsibilities
Lead the technical delivery of AI agent capabilities reusable platform components integrations and automation workflows.
Translate solution architecture into detailed engineering designs sprint plans and implementation tasks.
Guide developers on AI patterns cloud-native implementation secure coding testability and performance Eligible to workimization.
Build and review core components such as agent orchestration services API layers RAG services tool connectors and model interaction modules.
Coordinate with architects product owners UX designers security SMEs and QA teams to drive end-to-end delivery quality.
Establish technical best practices coding standards review processes and reusable accelerators.
Support environment readiness deployment planning defect triage production readiness reviews and knowledge transition.
Collaborate with enterprise architecture security data cloud platform application and business teams to ensure alignment with client standards.
Embed application security and cloud security requirements into solution design including IAM encryption network controls API protection secrets management secure data access logging and monitoring.
Drive build-versus-buy evaluations technology selection platform design decisions security trade-off analysis and architectural risk mitigation.
Establish reusable cloud patterns secure integration standards deployment approaches and non-functional requirements for performance resiliency and security.
Review detailed designs and implementation outputs to ensure adherence to approved architecture security controls and operational readiness expectations.