Lead AI Engineer – Cloud Infrastructure, Automation

Jobtailor

New Jersey

On-site

USD 150,000 - 210,000

Full time

14 days+

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Job summary

Jobtailor seeks a technical leader to accelerate delivery of solutions by building AI systems that generate, validate, and ship infrastructure-as-code—Terraform in particular. You will architect agentic applications on AWS and drive intelligent automation across cloud operations, setting standards and mentoring engineers while staying hands-on.

Responsibilities include integrating AI-assisted generation into CI/CD, curating reusable Terraform modules, and advancing agentic techniques to improve

Qualifications

Master's degree required.
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.

Responsibilities

Accelerate delivery of business-unit solutions by building AI systems that generate, validate, and ship infrastructure-as-code – Terraform in particular.
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.

Skills

AI Agent Development

Infrastructure Automation

Policy-As-Code

Context Engineering

RAG Pipelines

AIOps

Prompt Engineering

Model Selection

Automated Validation

Multi-Agent Systems

Education

Master's Degree

Tools

GitHub

Jenkins

Artifactory

SonarQube

LangChain

Amazon Bedrock Agents

ITSM Tools

Cloud Automation Platforms

Job description

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.

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