AI Engineer

AI Engineer (Remote) | Architect Enterprise Copilots & Agentic Workflows

Imagine engineering intelligent AI agents that automate complex enterprise workflows across millions of touchpoints. As an AI Engineer for our client, you’ll bridge the gap between AI/ML innovation, agentic orchestration, and production MLOps. If you’re ready to deploy cutting-edge LLM pipelines, custom Copilots, and scalable AWS/Azure solutions in a 100% remote environment, this is your next career move.

At-a-Glance Snapshot

• Role: AI Engineer (Agentic AI & MLOps)
• Location: 100% Remote
• Tech Ecosystem: Microsoft Copilot Studio, Power Platform, AWS SageMaker, Azure OpenAI, Python
• Impact: High-visibility enterprise AI automation across core financial and business platforms

Why Join Our Client?

Our client is rapidly expanding its enterprise AI capabilities, embedding intelligent agents into the heart of their digital operations. You’ll work at the intersection of production MLOps and next-gen agentic workflows—with total remote flexibility and strong growth potential.

• Cutting-Edge Tech Stack: Build with LLMs, RAG architectures, Copilot Studio, Vector DBs, and AWS/Azure ML infrastructure.
• True Autonomy & Ownership: Take AI models from experimental prototypes to high-availability, production-grade solutions.
• Enterprise Innovation: Solve real-world automation challenges in complex financial and business ecosystems.

Your Impact (The "Power" Bullets)

In this hybrid AI/ML and Platform Engineering role, you will:

• Build & Orchestrate Agents: Design custom Copilots, RAG pipelines, and intelligent agents in Copilot Studio that seamlessly connect to enterprise APIs.
• Automate Business Workflows: Integrate custom AI models into Power Apps and Power Automate to streamline critical operational processes.
• Scale Production MLOps: Automate end-to-end ML training, CI/CD, and monitoring pipelines on AWS SageMaker and Azure ML using Docker and Kubernetes.
• Drive AI Governance: Implement robust monitoring frameworks to track model drift, performance analytics, explainability, and data privacy.
• Elevate Engineering Standards: Collaborate across software engineering, IT, and security teams while mentoring junior engineers on AI tools and best practices.

What You Bring

We are seeking a versatile developer who combines strong Python/ML fundamentals with practical cloud and agent deployment experience.

• Experience: 2–5 years of hands-on experience spanning Software Engineering (preferred background in MS Stack), Machine Learning, or MLOps.
• Core Skills: Advanced Python proficiency alongside frameworks like PyTorch, Scikit-learn, or TensorFlow.
• Microsoft & AWS Stack: Demonstrated experience building with Copilot Studio, Power Platform, and deploying via AWS SageMaker or Azure ML.
• GenAI Knowledge: Familiarity with LLM orchestration, prompt engineering, vector databases (Pinecone, FAISS), and RAG architecture.
• Education: Bachelor’s or Master’s in Computer Science, Data Science, or a related technical field.
• Bonus Points: Background in financial/insurance domains or certifications like Azure AI Engineer Associate (AI-102) or AWS ML Specialty.

Ready to Shape the Future of Enterprise AI?

If you thrive on turning complex AI concepts into scalable, secure, and production-ready intelligent systems, we want to hear from you.