AWS Cloud Platform & DevOps Engineer (GenAI Platform)

SWIFT
Warren, NJ, United States
2 days ago
Apply on www.careerjet.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$76,960.0 - $83,200.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Data Analysis Application Services Automation of Tests Unit Testing Microsoft Azure Static Program Analysis Code Coverage Software Quality Continuous Integration
+42 more
Data Integration Software Debugging DevOps Github Monitoring of Systems Identity and Access Management IP Routing Subnetting PostgreSQL Routing Redis Release Management Reliability Engineering Runbook SonarQube Automatic Programming AWS Cdk Data Logging Load Balancing Cyberark Amazon ElastiCache Delivery Pipeline Large Language Models Software Security Cloudformation Amazon Relational Database Service AI Platforms Gitlab-ci Kubernetes Infrastructure Automation Frameworks Information Technology Performance Monitor Cloud Migration Virtual Agents Functional Programming Cloudwatch Api Gateway Terraform Dynatrace Docker Jenkins Vulnerability Analysis

Job description

Join us as an AWS Cloud Platform & DevOps Engineer (GenAI Platform) - Contractor within the IB Analytics team. The role owner will be responsible for hands-on design, provisioning, automation, deployment, monitoring, and production-readiness of the AWS platform supporting AI agents, MCP services, skills, orchestration components, and data integrations. The successful candidate will bring deep practical expertise across AWS, ECS, EKS, Kubernetes, CloudFormation, IAM, CI/CD pipelines, SonarQube, ESAAS, observability, and secure deployment automation., Design, provision, enhance, and maintain AWS environments supporting core platform services, agents, MCP servers, skills, and orchestration components. Build and configure ECS and EKS platforms, including Kubernetes deployment standards, ingress, load balancing, scaling, namespace design, and environment separation. Automate infrastructure provisioning using CloudFormation, AWS CDK, Terraform, or equivalent infrastructure-as-code tooling. Configure VPCs, subnets, route tables, ACLs, security groups, API Gateway, load balancers, S3, RDS/PostgreSQL, ElastiCache, Lambda, Systems Manager, Parameter Store, and Secrets Manager. Design and implement IAM roles, permission boundaries, service roles, system accounts, and secure cross-service access patterns. Build and manage CI/CD pipelines for BankerOne core platform, agents, MCPs, skills, and supporting services across non-production and production environments. Integrate automated unit-test checks, test coverage, code quality gates, SonarQube, static scanning, security checks, and deployment governance into delivery pipelines. Implement controlled deployment approaches where appropriate for platform and application services. Implement CloudWatch dashboards, logging pipelines, alerting, tracing, performance monitoring, availability monitoring, and ESAAS integration. Support security validation, resilience checks, production readiness, runbook creation, knowledge transfer, and RTB handover activities.

Requirements

Strong hands-on experience in AWS cloud platform engineering, DevOps, or site reliability engineering. Deep expertise with ECS, EKS, Kubernetes, Docker, container networking, orchestration, scaling, and deployment patterns. Proven experience with CloudFormation and infrastructure-as-code automation; experience with AWS CDK or Terraform is highly relevant. Strong working knowledge of AWS networking including VPCs, subnets, routing, ACLs, security groups, API Gateway, and load balancers. Strong knowledge of IAM, service roles, permission boundaries, Secrets Manager, Systems Manager, Parameter Store, and secure credential management. Experience with PostgreSQL/RDS, S3, ElastiCache/Redis, Lambda, CloudWatch, API Gateway, and related AWS managed services. Strong CI/CD experience using Jenkins, GitLab CI/CD, GitHub Actions, Harness, Azure DevOps, or similar tooling. Experience implementing SonarQube, static code analysis, security scanning, automated test checks, and quality gates. Experience implementing logging, monitoring, alerting, dashboards, and operational telemetry for production services. Ability to independently troubleshoot complex deployment, networking, IAM, Kubernetes, pipeline, runtime, and observability issues. Experience working in globally distributed agile teams with strong ownership and delivery accountability. Bachelor degree in a technical discipline such as Computer Science, Engineering, or equivalent experience. Desirable / Good to Have Skills Experience deploying GenAI, LLM, agentic AI, MCP, or data-intensive workloads on AWS. Working knowledge of AWS Bedrock, model-hosted application patterns, inference workloads, or AI platform services. Experience with OpenTelemetry, distributed tracing, structured logging, and enterprise observability platforms. Experience with blue-green deployment, canary deployment, automated rollback, and controlled production release patterns. Familiarity with enterprise security, architecture, cloud adoption, governance, and production-readiness review processes. Experience supporting RTB handover, ResCat validation, runbook creation, service monitoring, and operational support documentation. Financial services, Investment Banking, front-office technology, or other regulated enterprise technology experience. Exposure to SonarQube, ESAAS, CyberArk, service accounts, secrets rotation, cost management, and cloud governance tools. Other Skills & Attributes Strong problem-solving mindset with the ability to debug complex cloud, network, deployment, and pipeline issues. Excellent communication skills and the ability to collaborate with application developers, architects, security teams, governance teams, and production support. Independent, reliable, and highly delivery-focused with strong ownership of platform readiness. Comfortable operating in a fast-paced, enterprise-controlled environment with multiple governance dependencies. Willingness to define reusable platform patterns, improve engineering standards, and contribute to team knowledge sharing.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

3:55 min

Demonstrating semantic routing thresholds with the Redis vector library

6:36 min

Funding open source through GitHub Accelerator and Sponsors

Stormy Peters · World Congress 2023

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

2:36 min

Managing new AI workloads for non-technical employees

Michael Coté Michael Coté · World Congress 2026 Europe

3:42 min

Comparing in-memory and Redis storage for cache scalability

Simone Sanfratello · World Congress 2022

Videos

See all

Related articles

See all