AI Automation Engineer

Details: Stefanini Group is hiring! Stefanini is looking for AI Automation Engineer -Remote For quick apply, please contact Vaibhav Srivastava; Ph: 248 936 1053 Vaibhav [email protected] W2 Candidates Only As a Contract Sr. Technical Analyst, you will be hands-on for performing technical analysis and troubleshooting on highly complex integrated systems, including diagnostic approaches, determining root causes, and identifying solutions. You will work with AI Agent Automation & AWS Production Support largely focused on monitoring and observability. Essential Responsibilities:

• This is a hands-on role. Applicants should not be managers or architects.
• Provide primary technical support to end user community for problems related to software, data issues, data communication and processing errors.
• Monitor application, production and/or implementation support, both technical and user, for new releases.
• Consult on application testing strategies, document observations and coordinate responses.
• Maintain project and application information including schedule, system scope, requirements, and other pertinent documentation. Make recommendations to management regarding process improvements. Coordinate the information flow between business owners and development staff. Coordinate tasks, functional reviews and application development sessions between the development site and technical work groups ensuring steps are executed timely.
• Document end-user interactions into the automated call logging tools for tracking and productivity purposes.
• Validate proposed technical approaches to system or application problem logs and make recommendations for mediation to management.

Details: Technical Skills Required: AI Agents & Automation:

• Hands-on experience building and deploying AWS AI Agents, specifically using Amazon Bedrock Agents.
• Experience designing Agent skills/action groups to extend agent functionality for specific operational tasks.
• Understanding of prompt engineering, knowledge bases, and agent orchestration within Bedrock.
• Experience integrating AI Agents with existing APIs and operational tooling.

AWS Production & Automation:

• Strong hands-on experience with core AWS services: Lambda, Bedrock, S3, IAM, CloudWatch, EventBridge, Step Functions.
• Experience automating AWS production environment tasks (auto-remediation, automated alert handling).
• Familiarity with Infrastructure-as-Code (Terraform/CloudFormation) for agent and automation infrastructure deployment.

Observability Integration:

• Experience integrating AI/automation solutions with observability stacks (CloudWatch, Grafana, Container Insights) to enable intelligent automated actions.

CI/CD & Platform Tools:

• Experience with GitLab CI/CD for automation/agent deployment pipelines.
• Working knowledge of Databricks for data access/integration supporting agent decision-making.

Governance & Compliance:

• Understanding of AI/ML governance considerations - model risk, data privacy, auditability - particularly within regulated/financial services environments.
• Ability to work within client’s security and compliance framework for AI/automation deployments.

Support & Enablement:

• Experience translating existing manual support processes/runbooks into automated workflows.
• Strong documentation skills for architecture, agent logic, and governance compliance.
• Ability to train support teams on new automated tools and workflows.

Preferred Qualifications:

• Prior experience with Amazon Bedrock (Agents, Knowledge Bases, Guardrails).

Requirements:

• Provide hands-on production support for applications running on Kubernetes and HPC clusters, including incident triage, root cause analysis, and resolution.
• Assess current production support processes and identify opportunities for automation using AI Agents.
• Design, build, and deploy AWS AI Agents (using Amazon Bedrock Agents) to automate repetitive support tasks, incident triage, and operational workflows.
• Develop Agent skills/action groups to extend AI Agent capabilities for specific support use cases (e.g., log analysis, alert correlation, automated remediation).
• Integrate AI Agents with existing observability and monitoring tools (CloudWatch, Grafana, Container Insights) to enable intelligent, automated responses to production issues.
• Collaborate with support, platform, and application teams to translate manual ru…