Lead AI Engineer – Observability

Jobtailor; California (MO); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks a senior GenAI architect to design, develop, and deploy enterprise-scale Generative AI solutions across Azure and AWS. You will lead end-to-end GenAI lifecycles, implement GenAIOps, build scalable Python microservices, and guide teams through architecture, evaluation of tools, and secure coding practices for regulated environments.

Strong background in LLMs, RAG, LangChain, LangGraph, Docker/Kubernetes, Terraform, and IaC is required, along with mentoring experience and

Qualifications

• Experience leading GenAI solution design and deployment.
• Proven ability to mentor senior engineers.
• Strong collaboration with product, risk, and security teams.

Responsibilities

• Design, develop, and deploy enterprise-scale GenAI solutions.
• Lead end-to-end GenAI lifecycle from architecture to deployment and optimization.
• Mentor and coach senior engineers and development teams.
• Partner with product, risk, and security stakeholders.

Skills

Technical leadership

Mentoring

Communication

Collaboration

Education

Bachelor’s Degree

Master’s Degree

Tools

LangChain

LangGraph

Docker

Kubernetes

Terraform

AWS Bedrock

Microsoft Foundry Agent Service

ARM/Bicep

Python

CI/CD

Job description

• • Design, develop, and deploy enterprise-scale Generative AI solutions


• • Leverage LLMs, RAG architectures, prompt engineering, and agentic AI workflows


• • Build intelligent systems using LangChain, LangGraph, AWS Bedrock, and Microsoft Foundry Agent Service


• • Evaluate emerging tools and frameworks to improve solution quality and innovation


• • Lead the end-to-end GenAI solution lifecycle from architecture and engineering through deployment, monitoring, observability, and optimization


• • Implement GenAIOps practices for scalability, reliability, and cost efficiency


• • Establish logging, evaluation, and feedback mechanisms for production AI systems


• • Architect and deploy GenAI applications across Azure and AWS


• • Design distributed systems supporting high-throughput, low-latency AI workloads


• • Use Docker, Kubernetes, Terraform, and ARM/Bicep


• • Develop scalable applications using Python and microservices architectures


• • Apply secure coding and robust data handling practices for regulated environments


• • Build and manage CI/CD pipelines for automated testing, deployment, and release management


• • Enforce code reviews, testing, and documentation best practices


• • Provide architectural leadership and guidance across GenAI initiatives


• • Drive design decisions for large-scale AI solutions


• • Mentor and coach senior engineers and development teams


• • Translate business requirements into scalable, secure, and resilient technical solutions


• • Partner with product, business, risk, and security stakeholders

Requirements

• Bachelor’s degree, or equivalent work experience


• Six to eight years of relevant experience


• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field


• 8+ years of experience in software engineering, platform engineering, or AI/ML solutions


• 2+ years hands‑on experience with GenAI technologies, including LLMs, RAG architectures, and vector databases


• Strong knowledge of agentic AI concepts and frameworks such as LangChain and LangGraph


• Experience with Azure and/or AWS


• Deep understanding of distributed systems and scalable architecture patterns


• Proficiency in Python and microservices‑based development


• Experience with Docker, Kubernetes, and Infrastructure as Code tools


• Demonstrated technical leadership and mentoring experience


• Ability to comply with U.S. Bank policies and procedures, including the Code of Ethics and Business Conduct and related workplace conduct and safety policies

Core Competencies

Demonstrates expertise in designing and deploying enterprise-scale Generative AI solutions, leveraging LLMs, RAG architectures, and cloud platforms like Azure and AWS. Proficient in Python, microservices development, and implementing GenAIOps practices for scalable and reliable AI systems.

Highest-signal resume keywords

• Generative AI Solutions Design


• LLMs and RAG Architectures


• Python and Microservices Development


• Azure and AWS Deployment


• Technical Leadership and Mentoring

ATS Optimization Keywords

Hard Skills

• Generative AI


• LLMs


• RAG Architectures


• Python


• Microservices


• Distributed Systems


• Secure Coding


• CI/CD Pipelines


• Infrastructure as Code


• Data Handling Practices

Soft Skills

• Mentoring


• Collaboration


• Communication

Certifications & Qualifications

• Bachelor’s Degree


• Master’s Degree

Industry Keywords

• AI/ML Solutions


• GenAIOps


• Scalability


• Reliability


• Cost Efficiency

Tools & Technologies

• LangChain


• LangGraph


• Docker


• Kubernetes


• Terraform


• AWS Bedrock


• Microsoft Foundry Agent Service


• ARM/Bicep