Note: The job is a remote job and is open to candidates in USA. Stefanini Group is hiring a Senior Technical Analyst for hands-on production support and technical analysis of complex integrated systems. The role focuses on building AWS AI agents to automate support workflows, integrating them with observability tools, and supporting secure, governed deployments.
Responsibilities
- 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
- 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 runbooks/SOPs into automated agent-driven workflows
- Ensure all AI Agent development and deployment aligns with client's security, risk, and regulatory requirements (data handling, model governance, access controls)
- Work with Databricks data pipelines to enable AI Agents to pull relevant operational/support data for decision-making
- Build CI/CD pipelines (GitLab) for agent deployment, versioning, and lifecycle management
- Document agent architecture, workflows, and decision logic for support teams and auditors
- Train and knowledge-transfer to internal support teams on how to use, maintain, and extend AI Agent capabilities
- Participate in ongoing production support as needed, ensuring continuity between manual and automated processes during transition
Skills
- Applicants should not be managers or architects
- 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
- 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
- Experience integrating AI/automation solutions with observability stacks (CloudWatch, Grafana, Container Insights) to enable intelligent automated actions
- Experience with GitLab CI/CD for automation/agent deployment pipelines
- Working knowledge of Databricks for data access/integration supporting agent decision-making
- 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
- 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
- Provide hands-on production support for applications running on Kubernetes and HPC clusters, including incident triage, root cause analysis, and resolution
- Strong experience in Agile delivery, requirements engineering, backlog development and refinement
- Strong experience in stakeholder engagement
- Experience working with distributed teams, and providers of software solutions
- Broad knowledge of application and data modelling techniques with the ability to identify root cause issues and appropriate solutions
- Strong experience working in Agile environment/SAFe framework and Agile management tools like Jira
- Excellent analytical and design skills
- Excellent verbal and written communication skills — able to train/mentor both technical and non-technical audiences
- Patient and effective teacher/mentor, comfortable repeating/simplifying technical concepts as needed
- Strong collaboration skills across cross-functional teams (support, platform engineering, security, end users)
- Self-starter who can work independently while also building up team capability through training
- Prior experience with Amazon Bedrock (Agents, Knowledge Bases, Guardrails)
Benefits
- Remote work arrangement
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