AI/ML Engineer

AI/ML Engineer

Employment Type: W2

Rate: $65–70/hr

Location: Scottsdale, AZ (Hybrid from Day 1)

Position Overview

We are seeking an experienced AI/ML Engineer to design, build, and operate AI/ML infrastructure and agentic AI systems. The ideal candidate will have hands-on experience building MCP servers and agents, integrating LLMs, implementing RAG pipelines, and deploying scalable AI applications in production using Google Cloud and Kubernetes.

Key Responsibilities

• Design, build, and operate MCP servers and MCP agents to host, orchestrate, and monitor AI/Agent workloads.
• Develop Agentic AI solutions, prompt engineering strategies, LLM integrations, and developer tooling.
• Own deployment, scaling, reliability, and cost optimization using Kubernetes, Docker, and Google Cloud Platform.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and retrieval tooling.
• Utilize LangChain and Langfuse for orchestration, tracing, observability, and evaluation.
• Develop APIs and SDKs for model access and AI agent orchestration.
• Design secure and reliable agent workflows with appropriate safety controls.
• Build prompt templates, evaluation frameworks, and optimize LLM performance.
• Integrate cloud-hosted and self-hosted LLM providers with unified adapters and telemetry.
• Develop internal developer tools including CLI utilities, simulators, local runners, and debugging tools.
• Manage containerized services using Docker and Kubernetes (GKE).
• Implement logging, monitoring, metrics, dashboards, tracing, and alerting for AI infrastructure.
• Create operational runbooks, incident response procedures, and improve system reliability.
• Design document chunking, embeddings, vector indexing, retrieval strategies, re-ranking, and context injection for RAG applications.

Required Skills & Experience

• 5+ years of Software Engineering experience using Python and/or Node.js
• Strong system design and production application development experience
• 2+ years of experience with Large Language Models (LLMs) and prompt engineering
• 2+ years of experience building Agentic AI applications
• 2+ years of hands-on experience implementing RAG (Retrieval-Augmented Generation) solutions
• Experience with embeddings, vector databases, and retrieval optimization
• 2+ years of experience using LangChain
• Experience with Langfuse or similar prompt/model observability platforms
• 5+ years of experience with Docker, Kubernetes, CI/CD, and Infrastructure as Code
• 2+ years of experience with Google Cloud Platform (GCP)
• Experience building and deploying scalable AI applications in production
• Strong understanding of observability, distributed systems, testing, and security best practices
• Experience reducing hallucinations, retrieval failures, and data leakage risks in RAG systems
• Experience working with vector databases and embedding providers
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or ArgoCD

Preferred Qualifications

• Experience developing enterprise AI platforms
• Experience optimizing AI infrastructure for scalability and cost efficiency
• Experience working with production-grade AI systems
• Strong troubleshooting and debugging skills
• Excellent communication and collaboration skills

Recruitment Notice

This position is with our client, Randstad, and we (ThinqSpot Inc.) are the authorized third-party recruiting partner for this opportunity. Applicants must apply through ThinqSpot Inc. We will coordinate interviews and guide candidates throughout the hiring process.

About ThinqSpot Inc.

ThinqSpot Inc. is a staffing agency specializing in connecting top technology professionals with our clients. In addition to supporting our clients' hiring needs, we also recruit for our internal projects and direct clients.

We provide highly qualified technology professionals to meet our clients' business requirements and do not share any candidate's information with any third party without the candidate's informed written consent.

Important: ThinqSpot Inc. never charges candidates any upfront fees or recruitment costs at any stage of the hiring process.