- Your primary mandate is to accelerate delivery of business-unit solutions by building AI systems that generate, validate, and ship infrastructure-as-code – Terraform in particular – so environments are stood up faster and more consistently.
- You will architect agentic applications and workflows on AWS, apply intelligent automation across the platform and cloud operations, and pioneer emerging agentic techniques.
- As a technical leader, you will set direction, establish standards and guardrails, and mentor engineers while remaining hands‑on with design and implementation.
Requirements
- Master's Degree
- Design and build AI agents and tools that generate, validate, and refactor infrastructure-as-code – Terraform in particular – to accelerate the delivery of business-unit solutions.
- Embed guardrails, policy-as-code, and automated validation into the generation workflow so generated infrastructure adheres to standards, security policy, and reusable module patterns before it reaches production.
- Reduce provisioning lead time and rework by integrating AI-assisted code generation and review into the CI/CD toolchain (GitHub, Jenkins, Artifactory, SonarQube).
- Curate and maintain a library of reusable Terraform modules, blueprints, and golden patterns that agents can compose to stand up new environments quickly and consistently.
- Architect and build agentic applications and multi-agent systems using modern agent frameworks (e.g., LangChain, Amazon Bedrock Agents) to automate infrastructure, platform, and operations workflows.
- Apply and advance emerging agentic techniques such as context engineering, agent harnesses, tool/function calling, and evaluation loops to improve agent reliability and autonomy.
- Implement RAG pipelines (retrieval-augmented generation) over internal knowledge sources – runbooks, architecture docs, Terraform modules, and ITSM history – to ground agent behavior.
- Establish patterns and standards for prompt/context engineering, model selection, evaluation, cost management, and responsible-AI guardrails (security, privacy, and hallucination controls).
- Apply AIOps for anomaly detection, event correlation, and automated remediation across the cloud estate and automation platform.
- Reduce mean-time-to-detect and mean-time-to-resolve by integrating AI into ITSM (ticket triage, classification, routing, and self-healing runbooks) to accelerate cloud operations.
- Own the LLMOps/agent-ops foundation for agentic AI workloads – pipelines, deployment, evaluation, monitoring, and lifecycle management – on AWS.
- Partner with security, data governance, and legal teams to ensure AI solutions meet compliance and responsible-AI requirements.
- Set technical direction, define the AI roadmap for the platform, and provide architecture governance.
- Mentor engineers, run design reviews, and grow agentic-AI capability across the team.
Core Competencies
Demonstrates expertise in building AI systems and infrastructure-as-code using Terraform, while applying intelligent automation and agentic techniques to enhance cloud operations. Proven ability to mentor engineers and set technical direction, ensuring compliance with security and responsible-AI standards.
Highest-signal resume keywords
- Terraform Infrastructure-As-Code
- AI Systems Design
- AWS Architecture
- CI/CD Toolchain Integration
- Agentic Applications Development
ATS Optimization Keywords
Hard Skills
- AI Agent Development
- Infrastructure Automation
- Policy-As-Code Implementation
- Context Engineering
- RAG Pipelines
- AIOps
- Prompt Engineering
- Model Selection
- Automated Validation
- Multi-Agent Systems
Soft Skills
- Technical Leadership
- Mentoring
- Collaboration
- Communication
- Design Review
Certifications & Qualifications
- Master's Degree
Industry Keywords
- Infrastructure-As-Code
- Cloud Operations
- AI Compliance
- Responsible-AI
- Security Policy
Tools & Technologies
- GitHub
- Jenkins
- Artifactory
- SonarQube
- LangChain
- Amazon Bedrock Agents
- ITSM Tools
- Cloud Automation Platforms