Applied AI Engineer

About Action1: Action1 is a premier, hyper-growth cloud technology leader and the industry’s most trusted autonomous endpoint management platform powering Fortune 500 enterprises globally. Cloud-native, infinitely scalable, highly secure, and configurable in minutes, Action1 pioneers autonomous operating system and third-party software patching alongside peer-to-peer distribution models and real-time vulnerability assessments without requiring a VPN. Recognized by Inc. 5000 as the fastest-growing private software entity in America, Action1 eliminates routine corporate IT labor, systematically prevents ransomware variants, and safeguards digital employee experience limits on a global scale.

Position Overview

We are seeking a highly autonomous, systems-minded Applied AI Engineer to design, build, and operate LLM-powered internal solutions, tools, automations, and customer-facing AI features end-to-end. In this hands-on engineering seat within our core R&D group, you will move far beyond simple prototype shells to deliver highly practical, production-ready AI capabilities that solve actual enterprise problems. You will hold complete technical ownership of the solution lifecycle—challenging assumptions, selecting libraries, defining service contracts, and implementing robust LLM evaluation workflows. This role demands a seasoned software engineer who can balance output quality, system latency, and token consumption costs across containerized cloud environments.

Key Responsibilities

• LLM Solution Engineering: Build, scale, and optimize internal automations, multi-service backend integrations, and customer-facing generative AI features from design up to production deployment.
• Evaluation Pipeline Architecture: Construct, maintain, and automate robust LLM evaluation workflows, designing quality baselines, safety safeguards, and automated regression detection guardrails.
• Backend & API Orchestration: Program scalable microservices and robust integrations leveraging Python, FastAPI, and PydanticAI to guarantee dependable service contracts and failure recovery.
• Production Database Governance: Manage high-volume production databases using PostgreSQL , driving schema design, database indexing, data migrations, and backup/restore protocols.
• System Observability & Guardrails: Own production systems monitoring, telemetry tracking via OpenTelemetry , performance tuning, and active incident response participation.
• Emerging AI Technology Triage: Evaluate emerging AI patterns, agentic workflows, and Retrieval-Augmented Generation (RAG) concepts, advocating for internal tool adoption when justified by real-world metrics.

Required Skills & Qualifications

• Strong foundational software engineering mechanics backed by hands-on operational ownership of production systems using Python .
• Demonstrated experience developing production-grade LLM applications, with an advanced understanding of context design, structured outputs, and LLM orchestration .
• Practical competency setting up LLM evaluation environments, including experimental design, gating parameters, regression metrics, and observability layers.
• Proven background building multi-service architectures and containerized applications using Docker and Docker Compose .
• Outstanding verbal and written communication mechanics, optimized to collaborate across R&D, Product, and Security cells.
• Location Context: 100% remote-first full-time operational framework tailored exclusively for qualified engineers permanently located within Cyprus, Serbia, or Montenegro (Budva) .

Preferred Strategic Indicators (Nice to Have)

• Hands-on experience engineering agentic systems, chunking models, vector embeddings, or RAG evaluation frameworks.
• Familiarity deploying and managing containerized instances across Amazon Web Services (AWS), utilizing EC2, ECR, S3, and AWS Lambda .
• Prior experience building lightweight administrative interface tools with Streamlit , writing test frameworks via pytest , or utilizing JavaScript/TypeScript.
• Background executing code isolation, process sandboxing for sensitive execution fields, or navigating B2B SaaS compliance structures.

What We Offer

• The exceptional professional canvas to directly pilot, configure, and scale high-impact AI infrastructure for a premier cybersecurity enterprise.
• Highly stable income metrics with a comprehensive employee benefits program and clear paths for rapid internal promotions.
• Profound work-from-home remote parameters backed by fully flexible working hours.
• A highly professional, flat-hierarchy engineering ecosystem focused on technical ownership, best practices, and continuous tool optimization.