Lead Artificial Intelligence Engineer – Development, Infrastructure

Jobtailor; Illinois; Hybrid; USD 140,000 - 210,000; Full time

Job summary

U.S. Bank seeks a senior software engineer to design, develop, and maintain AI-enabled products, focusing on GenAI workflows, RAG pipelines, and vector databases. You will implement scalable, cost-conscious architectures and ensure high-quality code through reviews and testing.

Role requires 6–8 years of software experience, strong Python/Java skills, and hands-on work with Docker, Kubernetes, and vector databases. Hybrid/onsite collaboration with cross-functional teams across the bank.

Qualifications

• Bachelor's degree in computer science, engineering, or related field or equivalent practical experience.
• Six to eight years of relevant software engineering experience.
• 2-3 years of containerization and orchestration with Docker and Kubernetes.

Responsibilities

• Design, develop, test, operate, and maintain software and AI-enabled products.
• Build production-ready, testable code for components, services, and AI workflows.
• Collaborate with engineering, product, data, and business teams to deliver features.

Skills

Generative AI

Python programming

Java programming

APIs

Collaboration

Learning mindset

Problem-solving

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

FAISS

Pinecone

Weaviate

OpenSearch

Azure AI Search

LangChain

LangGraph

Neo4j

Job description

• Design, develop, test, operate, and maintain software and AI-enabled products
• Develop production-ready, testable code for assigned components, services, and AI workflows
• Build and integrate Generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Develop and enhance agentic AI systems that plan, reason, retrieve information, and invoke tools under defined guardrails
• Follow architectural patterns and best practices for scalability, reliability, performance, and cost
• Troubleshoot model/output quality issues and conduct root-cause analysis for software and AI components
• Make implementation decisions with customer and employee experience in mind
• Incorporate code review feedback and meet engineering, security, and compliance standards
• Participate in code reviews as author and reviewer
• Apply compliance, risk, data privacy, security, SRE, and AI evaluation practices
• Explore emerging GenAI, agentic framework, and vector search technologies through ideas, prototypes, and proofs of concept
• Communicate progress, blockers, and risks while delivering incremental features
• Collaborate with engineering, product, data, business teams, vendors, and stakeholders

Requirements

• Bachelor's degree in computer science, Engineering, or related field, or equivalent practical experience
• Six to eight years of relevant software engineering experience
• 10+ years of overall software development experience in Python and Java or other object-oriented languages
• 3+ years leading software projects with enterprise-level solutions
• 2-3 years of containerization and orchestration experience with Docker and Kubernetes
• Experience with Bedrock, LLMs, and vector databases
• 2-3 years of hands-on experience with Generative AI use cases, including RAG architectures, prompt engineering, and evaluation approaches
• Experience building and integrating vector databases such as FAISS, Pinecone, Weaviate, OpenSearch, or Azure AI Search
• Exposure to agentic AI concepts including multi-step reasoning, tool invocation, workflow orchestration, and AI agents
• Practical experience with LangChain and LangGraph, including complex agent workflows and RAG pipelines
• 2-3 years of experience building data-driven APIs and services using Python
• Working knowledge of Agile software development lifecycle and DevOps practices
• Understanding of AI-powered features' impact on workflows, decision-making, and trust
• Growing understanding of responsible AI principles, model limitations, and guardrails in regulated environments
• Ability to collaborate across engineering, product, data, and business teams
• Technical proficiency defining and implementing solution requirements for end users
• Ability to communicate processes, design decisions, and results to technical and business stakeholders
• Solid understanding of algorithms, data structures, architectural design patterns, and best practices
• Strong analytical, problem-solving, and learning mindset
• Familiarity with Knowledge Graph concepts and graph databases such as Neo4j or TigerGraph is a plus
• Familiarity with modern UI frameworks such as React is a plus
• Ability to work from a U.S. Bank location three or more days per week
• Applicants must comply with U.S. Bank policies, procedures, Code of Ethics, workplace conduct, and safety policies

Core Competencies

Demonstrates expertise in developing and integrating Generative AI solutions, including Retrieval-Augmented Generation (RAG) architectures and vector databases. Proficient in Python and Java, with a strong understanding of software engineering principles, compliance standards, and collaborative practices across cross-functional teams.

Highest-signal resume keywords

• Generative AI Solutions Development
• Python and Java Programming
• Containerization with Docker and Kubernetes
• Vector Database Integration
• Agile Software Development

ATS Optimization Keywords

Hard Skills

• Software Development
• Generative AI
• RAG Architectures
• Vector Databases
• API Development
• Data Structures
• Algorithms
• AI Evaluation Practices
• Code Review
• Problem-solving

Soft Skills

• Collaboration
• Communication
• Analytical Mindset
• Learning Mindset
• Customer Experience Focus

Industry Keywords

• AI Systems
• Data Privacy
• Security Standards
• Compliance
• Agile Methodologies
• DevOps Practices
• Agentic AI
• Knowledge Graph
• Graph Databases
• U.S. Bank Policies

Tools & Technologies

• Docker
• Kubernetes
• FAISS
• Pinecone
• Weaviate
• OpenSearch
• Azure AI Search
• LangChain
• LangGraph
• Neo4j