Remote Ai Agent Engineer: Post-Training

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you

ABOUT THE ROLE

We are looking for an Agentic AI Engineer to build generative AI workflows that automate cloud configuration baselines and remediation.

The mandatory requirements are 4+ years of software engineering experience on public cloud infrastructure, 2+ years with cloud deployment pipelines and Infrastructure as Code, 2+ years developing agentic models using RAG and vector databases, and the ability to partner with globally distributed engineering teams.

MUST HAVES

• 4+ years of software engineering experience developing applications and services hosted on public cloud infrastructure.
• 2+ years of experience with cloud infrastructure deployment pipelines and infrastructure as code (IaC).
• 2+ years of experience developing Agentic models (e.g., OpenAI, Anthropic) using Retrieval-Augmented Generation (RAG) and Vector databases.
• Proven capability to partner with globally distributed inter-disciplinary engineering teams.

NICE TO HAVES

• Hands‑on experience with modern AI orchestration frameworks (LangChain, LangGraph).
• Hands‑on experience writing Rego policies (Open Policy Agent) or Regula test cases.
• Hands‑on experience with Terraform.
• Familiarity with cloud‑native security services in Amazon Web Services, Azure, and Google Cloud Platform.
• Familiarity with PagerDuty, Atlassian Suite, and Service Now.

WHAT YOU WILL DO

• AI Acceleration: implement generative AI workflows utilizing RAG, vector databases, and LLM APIs to automate the creation of cloud configuration baselines.
• Cloud Security Automation: develop AI‑enabled drift detection, continuous discovery, and gap analysis capabilities to accelerate response and remediation activities.
• Policy & Infrastructure as Code (IaC): generate and validate compliant Terraform modules, Rego policies (for Wiz Custom Configuration Rules), and Regula test cases for CI/CD pipelines.

PERKS AND BENEFITS

• Professional growth : mentorship, TechTalks, and personalized growth roadmaps.
• Competitive compensation : USD‑based pay with education, fitness, and team activity budgets.
• Exciting projects : modern solutions with Fortune 500 and top product companies.
• Flextime : flexible schedule with remote and office options.

Spoiler: This is where your next big move begins.

What this Journey Looks Like

At Pearster, we are hiring an AI Engineer to join our team. This is a 100% remote position where you will be responsible for designing, building, and implementing AI‑powered solutions that solve real business challenges and create meaningful impact.

You will work with modern Artificial Intelligence technologies, including Generative AI, Large Language Models (LLMs), Machine Learning, and intelligent automation, collaborating with cross‑functional teams to transform ideas and business needs into scalable, production‑ready solutions.

We are looking for a curious, hands‑on, and innovative professional who enjoys experimenting with emerging technologies, solving complex problems, and turning the latest advances in AI into practical solutions.

What You'll Lead and Build

Build solutions leveraging Generative AI, Large Language Models (LLMs), and Machine Learning.

Design, develop, and deploy AI‑powered applications and solutions.

Develop and integrate AI agents, APIs, and intelligent automation workflows.

Build solutions using RAG (Retrieval‑Augmented Generation), embeddings, vector databases, and prompt engineering.

Integrate AI models and services from platforms such as OpenAI, Anthropic, Google, AWS, Azure, or similar providers.

Develop prototypes and Proofs of Concept (POCs) and help transform successful experiments into production‑ready solutions.

Evaluate and optimize AI solutions for accuracy, reliability, performance, scalability, and cost.

Collaborate with Engineering, Product, and business stakeholders to identify opportunities where AI can create meaningful value.

Integrate AI capabilities into existing applications, platforms, and workflows.

Contribute to responsible AI practices, including security, privacy, monitoring, and appropriate use of AI systems.

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