AI Solutions Engineer - Associate

Company
Federal Reserve Bank of Richmond
When you join the Federal Reserve—the nation's central bank—you’ll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we’re building a dynamic and diverse team for our future.
We invite applications for AI Solutions Engineer - Associate
The AI Solutions Associate Engineer role is ideal for early-career professionals looking to build a career in supporting the development and maintenance of AI/ML solutions using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks, combined with Infrastructure as Code and automation practices. The engineer will contribute to building and supporting scalable, secure AI-powered systems for the Federal Reserve System under the guidance of senior team members.
Infrastructure Platforms & Operations:
You will be joining The Infrastructure, Platforms & Operations portfolio. This business line supports the strategic direction and product delivery for System IT infrastructure and operations, as well as the alignment of technology to business strategies. The team serves as the business partner for secure and reliable IT products, services, and operations.
This position does not sponsor employment visas. Candidates must be U.S. citizens or lawful permanent residents with at least three years of legal residency.
There are three (3) vacancies for this job profile, candidates will be selected based on the needs of the position and the strength of the candidate pool.
AI/ML Solution Development
Work under close direction and guidance; follow established methods and policies.
Contribute to RAG pipelines, prompt engineering, and agentic workflows to support business use cases
Write automation scripts using Python to help streamline AI model deployment, data pipelines, and operational processes
Assist in building and deploying GenAI, RAG, and Agentic AI solutions leveraging AWS Bedrock and related AI/ML services, under guidance from senior engineers
Support configuration of AWS infrastructure for AI workloads including compute, storage, networking, and security using Terraform and Infrastructure as Code (IaC) principles
Support and maintain CI/CD pipelines for automated testing, deployment, and infrastructure provisioning using GitLab or similar tools

Application Development & Support
Assist in developing user interfaces using React for AI front end, monitoring solutions, and administrative applications
Help troubleshoot and resolve routine to moderately complex AI infrastructure and application issues
Code, test, debug, and document AI/ML pipeline components and infrastructure enhancements
Produce ad-hoc queries, reports, and simple automation tools as requested by technical teams and business management
Support system health checks and basic troubleshooting to help ensure reliability of deployed solutions

Collaboration & Process Improvement
Work as part of an Agile team, contributing to AI capabilities that support business processes and decision-making
Participate in design reviews and team discussions, raising questions and sharing observations
Support change and problem management activities using standard tools, following FRIT change management policies and procedures
Assist with analysis of business requirements as they relate to AI solutions
Help document AI solution details, runbooks, and operational procedures following technical writing best practices

Minimum qualifications: 0 to 3 years of direct relevant work experience in AI/ML engineering, cloud infrastructure, DevOps, or software engineering
OR
a bachelor's degree in computer science, Information Technology, Engineering, or related field preferred.
Information technology Interns with a BA degree and a strong technical foundation, from their internship experience, and relevant coursework in AI/ML are encouraged to apply

What we are looking for: Foundational knowledge of Generative AI concepts, Large Language Models (LLMs), and prompt engineering
Basic exposure to Retrieval-Augmented Generation (RAG) concepts and vector databases
Basic understanding of Agentic AI concepts and orchestration patterns
Working knowledge of Python for scripting and automation
Basic proficiency with Terraform or similar Infrastructure as Code tools
Familiarity with core AWS services (EC2, S3, Lambda, VPC, IAM)
Basic understanding of CI/CD concepts and tools such as GitLab
Basic knowledge of React for frontend development
Understanding of version control systems (Git) and collaborative development workflows
Basic knowledge of SQL queries and data analysis techniques
Certification related to Information Technology or AI/ML preferred (AWS Certified Cloud Practitioner, HashiCorp Certified: Terraform Associate, AWS AI Practitioner, or similar)

Technical Competencies: General knowledge of cloud computing concepts and AI/ML system basics
Basic understanding of networking fundamentals and security principles
Willingness to learn and grow problem-solving skills to debug technical issues with guidance
Ability to follow technical standards and engineering best practices
Basic awareness of performance measures and metrics relevant to system health (nice to have)

Professional Competencies: Strong written and verbal communication skills with attention to detail
Ability to document technical work clearly for technical and non-technical audiences
Collaborator who is cooperative and open to feedback and mentorship
Demonstrates enthusiasm for learning new AI technologies and staying current with industry trends
Basic understanding of risk management principles in decision-making, particularly regarding responsible AI use

In addition to meeting the above requirements the following are nice to have but not required:
Coursework, projects, or internship exposure to AWS Bedrock or GenAI/RAG applications
Exposure to AI agent frameworks (e.g., LangChain, LangGraph, or similar)
Basic knowledge of vector databases and embedding models
Familiarity with containerization technologies (Docker, ECS, EKS)
Exposure to API development and RESTful services
Familiarity with Agile methodologies
General familiarity with monitoring and observability concepts (e.g., logging, metrics, alerting, dashboards) and related tools such as CloudWatch, Grafana, or similar platforms
Additional Information:
The full salary range for the Associate Engineer job profile: $76,000-$95,800.00-$124,500.00.
The candidate’s new job title and associated pay range will be determined by the employing District, and they will be subject to the employing District’s people policies and practices.
As a Federal Reserve System National Business Line, it is standard practice to post System IT positions in multiple Districts to provide transparency and equitable opportunities. Internal candidate(s) selected for this position will remain employed by their current employing District and serve as an employee of System IT*.
*Current remote employees will not be guaranteed to keep their remote status with their employing bank. The selected candidate will reside within a reasonable commuting distance, as defined by the employing Reserve Bank, and will work full-time onsite.
Eligible Locations for Hire:  Boston, MA- New York, NY- Philadelphia, PA- Cleveland, OH- Richmond, VA- Atlanta, GA- Chicago, IL- St. Louis, MO- Minneapolis, MN- Kansas City, MO- Dallas, TX- San Francisco, CA
OR

The following Reserve Bank locations are preferred due to the concentration of System IT team members in these locations: Atlanta, Boston, Chicago, Kansas City, Minneapolis, New York, Richmond, and San Francisco. (example for limited posting locations)
Screening:
This position has additional screening requirements due to the information accessed while performing the job. These additional screenings would be initiated