Job ID: JOB_ID_2006
Role Overview: AI/ML Engineer (Agentic Systems & Infrastructure)
As we move into 2026, the landscape of Artificial Intelligence has shifted from simple LLM wrappers to complex, autonomous agentic systems. We are seeking a Senior AI/ML Engineer to join our team in Scottsdale, AZ, on a hybrid basis. This role is pivotal in designing, building, and operating the next generation of AI infrastructure. You will be at the forefront of developing Model Context Protocol (MCP) servers and agents, which are essential for hosting and orchestrating sophisticated AI workloads. Your expertise will help us bridge the gap between raw model capabilities and production-ready, reliable AI services. In this era of rapid technological evolution, the ability to build scalable and resilient systems is more important than ever. You will be working with a team of highly skilled engineers and data scientists to push the boundaries of what is possible with AI. This position offers the unique opportunity to work on cutting-edge projects that have a direct impact on our clients’ success. We are looking for someone who is not only a technical expert but also a strategic thinker who can anticipate future trends and challenges in the AI space.
Key Responsibilities and Technical Depth
- MCP Server & Agent Development: You will own the lifecycle of MCP servers, ensuring they are robust enough to handle high-volume agentic workloads. This involves not just coding but architecting the orchestration and monitoring frameworks that keep these agents performing optimally. You will need to ensure that these servers are highly available and can scale seamlessly as demand increases.
- Agentic AI & Prompt Engineering: Beyond basic prompting, you will implement advanced patterns such as Chain-of-Thought, grounding strategies, and safety guardrails. You will develop the developer tooling necessary to test and iterate on these templates in a simulated environment before they hit production. This requires a deep understanding of how different models respond to various prompts and how to optimize them for specific tasks.
- RAG Pipeline Architecture: You will design and implement Retrieval-Augmented Generation (RAG) pipelines. This includes managing document chunking strategies, embedding generation, and vector indexing. You will use tools like LangChain for orchestration and Langfuse for deep observability into the retrieval process, ensuring that hallucinations are minimized and context injection is precise. The goal is to provide the AI with the most relevant and accurate information possible to improve its performance.
- Cloud Infrastructure & DevOps: Operating on Google Cloud Platform (GCP), you will manage containerized services using Docker and Kubernetes (GKE). You will be responsible for autoscaling, resource optimization, and maintaining automated CI/CD pipelines using Jenkins or GitHub Actions. You will also need to ensure that the infrastructure is secure and compliant with industry standards.
- Observability & Reliability: In the world of AI, observability is paramount. You will establish SLOs, create comprehensive dashboards, and develop incident response procedures to reduce MTTR. You will perform post-mortems on system failures to continuously improve the reliability of our AI infrastructure. This involves monitoring not just the infrastructure but also the performance of the AI models themselves.
Required Qualifications and Experience
- A minimum of 5 years in professional software engineering, with a heavy focus on Python or NodeJS and distributed system design.
- At least 2 years of hands-on experience with Large Language Models (LLMs) and agent frameworks.
- Proven track record of implementing RAG systems, including experience with vector databases and retrieval tuning.
- Deep familiarity with Kubernetes, Docker, and Infrastructure as Code (IaC) principles.
- Experience with GCP services and observability tools like Langfuse or similar telemetry platforms.
- Strong understanding of security best practices for AI systems, including mitigating data leakage risks.
- Excellent problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.
This position requires a candidate who is not only technically proficient but also a visionary in the AI space. You will be expected to stay ahead of vendor updates and open-source vector store advancements to ensure our stack remains cutting-edge. The ideal candidate will have a passion for building scalable, cost-efficient, and highly reliable AI systems that provide real-world value. You will be part of a culture that values innovation, collaboration, and continuous learning. We offer a competitive salary and benefits package, as well as opportunities for professional growth and development. If you are a talented AI/ML engineer looking for a new challenge, we encourage you to apply.
Special Requirements
US Citizen ONLY. Hybrid Scottsdale. Client: TCS. No fake GCs.
Compensation & Location
Salary: $125,000 – $165,000 per year (Estimated)
Location: Scottsdale, AZ
Recruiter / Company – Contact Information
Recruiter / Employer: TechOne IT
Email: tripti@techoneit.com
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