AI Infrastructure Engineer (Forward Deployed AI Engineer)

Responsibilities:

Embed within infrastructure teams to understand workflows and identify automation opportunities.
Independently identify and implement automation solutions.
Build AI-assisted solutions utilizing Cursor and GitHub Copilot.
Develop infrastructure automation processes to streamline operations.
Create AI workflows and AI agents to enhance productivity.
Modernize existing infrastructure platforms for improved performance.
Enhance cloud migration efficiency through innovative solutions.
Automate vulnerability remediation processes.
Mentor existing engineering teams on best practices and AI adoption.
Promote AI adoption across the organization to drive efficiency.
Deliver measurable productivity improvements through automation.
Rapidly demonstrate proof-of-concepts to stakeholders.
Collaborate closely with business and infrastructure leaders to align on goals.
 

Mandatory Skills:

Strong proficiency in Python development.
Experience in infrastructure engineering.
Familiarity with cloud platforms, preferably AWS.
Expertise in Infrastructure as Code (IaC).
Proficient in GitHub Copilot and Cursor AI.
Knowledge of prompt engineering and LLM-based software development.
Experience with AI-assisted coding practices.
Strong understanding of DevOps principles and automation.
Proficient in APIs and scripting.
Excellent problem-solving skills and a self-starter mindset.
Strong communication skills to convey complex ideas effectively.
 

Preferred Skills:

Experience with agentic AI workflows and AI orchestration.
Knowledge of infrastructure modernization techniques.
Familiarity with security automation and vulnerability management.
Understanding of FinOps and observability practices.
Experience in platform engineering and cloud migration strategies.
 

Qualifications:

3-5 years of relevant experience in AI infrastructure engineering.
Proven track record of delivering automation solutions that reduce manual effort.
Demonstrated ability to influence and mentor engineering teams.
Strong collaborative skills and ability to work in ambiguous environments.
Outcome-focused with a commitment to driving measurable improvements.
 

Success Measures:

Reduction of manual effort by 50-70% through automation.
Increased AI adoption across teams and projects.
Successful delivery of infrastructure automation initiatives.
Faster project execution and improved engineering productivity.
Positive influence on engineering culture and practices.
 

Desired Behavioral Traits:

AI-native mindset with a passion for innovation.
Highly proactive and curious about emerging technologies.
Independent thinker who can navigate ambiguity.
Strong collaborator with the ability to influence others.
Outcome-focused and committed to achieving results.