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Associate Principal, AI Engineer
Request Technology, LLC
3 hours ago
Full-time
On-site
Chicago, Illinois, United States
Associate Principal, AI Engineering
Check below to see if you have what is needed for this opportunity, and if so, make an application asap.
*We are unable to sponsor for this permanent Full-time role* *Position is bonus eligible*
Location:
Chicago, IL Work Arrangement:
Hybrid (3 days on site)
We are seeking an
Associate Principal, AI Engineering
to help build and evolve next-generation
agentic AI capabilities
within a highly regulated enterprise environment. This is an opportunity for an experienced engineer who is interested in AI and wants to help shape a growing AI engineering function. You don't need to be an expert across every area — we're looking for
depth in at least one of three areas: Data Engineering, Software/Application Engineering, or Infrastructure Engineering , along with strong communication and collaboration skills.
What You'll Do Design, build, and deploy
AI-powered applications and agentic workflows
from architecture through production. Help develop the data and technology foundation that makes enterprise information consumable by AI models. Build
data pipelines and ETL/ELT processes
across enterprise sources such as ServiceNow, Jira, and SaaS applications. Design agent orchestration, tool integrations, context management, and evaluation workflows. Build and support
AWS infrastructure
for AI applications and services. Develop scalable, production-ready solutions using modern engineering practices, APIs, containers, and CI/CD. Implement safeguards for AI-specific risks including
prompt injection, hallucinations, data privacy, and output validation . Build audit logging and human-in-the-loop controls for AI workflows operating in a regulated environment. Partner with business and technical stakeholders to translate complex requirements into practical solutions. Mentor early-career engineers through technical guidance, code reviews, and architecture reviews. Help establish engineering standards and best practices for a rapidly evolving AI organization.
Three Engineering Paths You don't need to be equally strong in all three. We're looking for
deep expertise in at least one : Data Engineering — Highest Current Priority ETL/ELT and enterprise data pipelines Data modeling and data integration Building a \"knowledge substrate\" that makes enterprise data accessible to AI Experience with data from platforms such as ServiceNow, Jira, and SaaS applications Software / Application Engineering Python and API development LLM-powered applications and agentic workflows Distributed systems and application architecture Agent orchestration and tool/context integration Infrastructure Engineering AWS cloud infrastructure Infrastructure as Code and automation Docker/containerization CI/CD and deployment pipelines Kubernetes is a plus
What We're Looking For 4–7+ years of software/data/infrastructure engineering experience
with ownership of production systems. Strong
Python
and proficient
SQL . Experience building
LLM-powered applications, AI solutions, or agentic systems
— deep AI experience is not required. Strong fundamentals in APIs, distributed systems, cloud infrastructure, or data engineering. Experience with
AWS
and modern engineering practices. Familiarity with
Docker, CI/CD, and containerization . Interest in emerging AI technologies and a willingness to learn quickly. Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders. Experience mentoring or supporting the development of other engineers.
Preferred Experience Anthropic Claude / Anthropic API
or OpenAI experience. Agent orchestration or
Model Context Protocol (MCP)
integrations. Kubernetes and Terraform. Production AI/LLM applications operating at scale. AI security, red-teaming, prompt-injection defense, or adversarial testing. Data engineering, data pipelines, or data modeling. Financial services or other highly regulated industry experience. Master's degree in Computer Science, Engineering, or a related technical field.
Why This Role? You'll have the opportunity to help build
enterprise-grade agentic AI from the ground up , working with technologies such as
Anthropic Claude and AWS
while helping establish the engineering practices, data foundation, and infrastructure needed to scale AI across the organization. This is a hands-on technical leadership opportunity where
AI interest, engineering fundamentals, communication, and the ability to mentor others
are just as important as having years of specialized AI experience. This position is not eligible for employment visa sponsorship. xsgimln Candidates must be legally authorized to work in the United States without the need for sponsorship now or in the future.
Check below to see if you have what is needed for this opportunity, and if so, make an application asap.
*We are unable to sponsor for this permanent Full-time role* *Position is bonus eligible*
Location:
Chicago, IL Work Arrangement:
Hybrid (3 days on site)
We are seeking an
Associate Principal, AI Engineering
to help build and evolve next-generation
agentic AI capabilities
within a highly regulated enterprise environment. This is an opportunity for an experienced engineer who is interested in AI and wants to help shape a growing AI engineering function. You don't need to be an expert across every area — we're looking for
depth in at least one of three areas: Data Engineering, Software/Application Engineering, or Infrastructure Engineering , along with strong communication and collaboration skills.
What You'll Do Design, build, and deploy
AI-powered applications and agentic workflows
from architecture through production. Help develop the data and technology foundation that makes enterprise information consumable by AI models. Build
data pipelines and ETL/ELT processes
across enterprise sources such as ServiceNow, Jira, and SaaS applications. Design agent orchestration, tool integrations, context management, and evaluation workflows. Build and support
AWS infrastructure
for AI applications and services. Develop scalable, production-ready solutions using modern engineering practices, APIs, containers, and CI/CD. Implement safeguards for AI-specific risks including
prompt injection, hallucinations, data privacy, and output validation . Build audit logging and human-in-the-loop controls for AI workflows operating in a regulated environment. Partner with business and technical stakeholders to translate complex requirements into practical solutions. Mentor early-career engineers through technical guidance, code reviews, and architecture reviews. Help establish engineering standards and best practices for a rapidly evolving AI organization.
Three Engineering Paths You don't need to be equally strong in all three. We're looking for
deep expertise in at least one : Data Engineering — Highest Current Priority ETL/ELT and enterprise data pipelines Data modeling and data integration Building a \"knowledge substrate\" that makes enterprise data accessible to AI Experience with data from platforms such as ServiceNow, Jira, and SaaS applications Software / Application Engineering Python and API development LLM-powered applications and agentic workflows Distributed systems and application architecture Agent orchestration and tool/context integration Infrastructure Engineering AWS cloud infrastructure Infrastructure as Code and automation Docker/containerization CI/CD and deployment pipelines Kubernetes is a plus
What We're Looking For 4–7+ years of software/data/infrastructure engineering experience
with ownership of production systems. Strong
Python
and proficient
SQL . Experience building
LLM-powered applications, AI solutions, or agentic systems
— deep AI experience is not required. Strong fundamentals in APIs, distributed systems, cloud infrastructure, or data engineering. Experience with
AWS
and modern engineering practices. Familiarity with
Docker, CI/CD, and containerization . Interest in emerging AI technologies and a willingness to learn quickly. Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders. Experience mentoring or supporting the development of other engineers.
Preferred Experience Anthropic Claude / Anthropic API
or OpenAI experience. Agent orchestration or
Model Context Protocol (MCP)
integrations. Kubernetes and Terraform. Production AI/LLM applications operating at scale. AI security, red-teaming, prompt-injection defense, or adversarial testing. Data engineering, data pipelines, or data modeling. Financial services or other highly regulated industry experience. Master's degree in Computer Science, Engineering, or a related technical field.
Why This Role? You'll have the opportunity to help build
enterprise-grade agentic AI from the ground up , working with technologies such as
Anthropic Claude and AWS
while helping establish the engineering practices, data foundation, and infrastructure needed to scale AI across the organization. This is a hands-on technical leadership opportunity where
AI interest, engineering fundamentals, communication, and the ability to mentor others
are just as important as having years of specialized AI experience. This position is not eligible for employment visa sponsorship. xsgimln Candidates must be legally authorized to work in the United States without the need for sponsorship now or in the future.