AI Solutions Engineer

Tech Sales Jobs; Atlanta (GA); Presencial; USD 80 000 - 95 000; Tempo integral

Resumo da oferta

Federal Reserve Bank of Richmond is seeking an experienced AI Solutions Engineer to design and maintain enterprise-scale AI/ML systems. You will implement GenAI, RAG, and agentic frameworks across AWS, leverage Terraform for infrastructure, and develop automation pipelines while collaborating across teams.

You will also contribute to architectural governance, security, and cost optimization, with opportunities to mentor junior engineers and drive impactful AI initiatives within the Federal

Qualificações

• Progressive experience building GenAI, RAG, and agentic AI solutions.
• Hands-on experience with AWS Bedrock and related AI/ML services.
• Strong programming in Python and Bash for automation and tooling.

Responsabilidades

• AI Solution Architecture & Engineering: Design AI/ML solutions across AWS with Terraform.
• CI/CD & Automation: Build GitLab pipelines and automate AI deployments.
• Problem Resolution & System Reliability: Troubleshoot AI infra and ensure reliability.
• Application Development & Integration: Develop React UIs and APIs for AI tools.
• Project Leadership & Collaboration: Lead AI infra projects and mentor engineers.
• Governance & Compliance: Adhere to FRIT change management and security best practices.

Conhecimentos

GenAI

RAG pipelines

AWS Bedrock

Python

Formação académica

Bachelor's degree

Ferramentas

Terraform

GitLab

React

Descrição da oferta de emprego

Location: Richmond, VA, St. Louis, MO, Cleveland, OH, Philadelphia, PA, East Rutherford, NJ, San Francisco, CA, New York, NY, Boston, MA, Minneapolis, MN, Atlanta, GA, Dallas, TX

Time Type: Full time

Job Description

Company

Federal Reserve Bank of RichmondWhen 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.

AI Solutions Engineer - Experienced

In this role you will be responsible for developing and maintaining enterprise-scale AI/ML solutions using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks, combined with Infrastructure as Code and automation practices. You will participate in design and implement scalable, secure, and efficient AI-powered systems supporting critical business functions across the Federal Reserve System. This position requires a moderate level of experience and proficiency in AI/ML technologies, cloud infrastructure, and DevOps practices.

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.

Why Join Us:

• Lead significant AI infrastructure initiatives at a critical national institution supporting the nation's financial system
• Work with cutting-edge Generative AI, RAG, and Agentic AI technologies alongside modern automation frameworks
• Opportunity to architect and implement enterprise-scale AI solutions with real business impact
• Mentorship opportunities with junior engineers while continuing to grow your own technical expertise
• Exposure to diverse technology stacks and complex problem domains across multiple business lines
• Collaborative environment that values innovation, continuous improvement, and public service
• Comprehensive benefits package, competitive compensation, and work-life balance
• Professional development support including training, certifications, and conference attendance

What You Will Do:

AI Solution Architecture & Engineering

• Develop conceptual, logical, and physical designs for AI/ML solutions using Terraform that support the infrastructure requirements of varying levels of technical and business application projects across AWS Cloud environments
• Design and implement complex GenAI, RAG, and Agentic AI solutions leveraging AWS Bedrock and related AI/ML services, along with supporting compute, storage, networking, and security infrastructure
• Architect RAG pipelines, vector database integrations, and multi-agent orchestration systems for production use cases
• Complete analysis of business requirements as they relate to AI solution design, and ensure traceability of the design to business requirements
• Assess testing requirements and prepare testing strategies, as well as implementation and transition plans for AI infrastructure changes
• Prepare detailed specifications and documentation from which AI infrastructure will be provisioned and maintained

CI/CD & Automation

• Design, implement, and maintain sophisticated CI/CD pipelines for automated testing, deployment, and infrastructure provisioning of AI solutions using GitLab
• Develop and maintain complex automation scripts using Python or Bash to streamline model deployment, data pipelines, and manual processes to improve operational efficiency
• Utilize available tools for automation of manual processes, contributing to increased team productivity
• Follow and ensure adherence to technical standards for AI solution design and automation techniques

Problem Resolution & System Reliability

• Perform resolution of complex AI infrastructure and application problems affecting system operations; initiate problem avoidance actions
• Analyze and revise existing system logic, AI pipeline patterns, and documentation as necessary
• Recommend solutions to minimize and/or prevent system interruption based on trend analysis and proactive system checks
• Support system health and performance reviews to help ensure reliability of deployed AI solutions

Application Development & Integration

• Develop user interfaces and internal tools using React for AI front end, monitoring solutions, and administrative applications
• Build and maintain APIs and integration services to support AI solution automation and orchestration
• Design, code, test, debug, document, and maintain moderately complex software enhancements to support AI infrastructure and pipelines

Project Leadership & Collaboration

• May indirectly lead moderately complex AI infrastructure projects and participate on technical/complex cross-functional projects
• Provide project updates and prepare management reports as required, tailored for both technical and business audiences
• Work and collaborate as part of an Agile team to develop and implement AI capabilities that enable business processes and decision-making
• Train technical staff on use of AI tools, Terraform, CI/CD pipelines, and related platforms in accordance with required standards and procedures
• Participate in design reviews, architecture discussions, and provide technical mentorship to junior engineers

Governance & Compliance

• Perform change and problem management using standard tools, following FRIT change management policies and procedures for AI infrastructure propagation to other platforms and/or environments
• Contribute to development and revision of department standards, procedures, and best practices
• Assist with monitoring compliance with internal audit requirements and Information Security Manual guidelines
• Ensure AI solution implementations adhere to security best practices, responsible AI principles, compliance requirements, and cost optimization strategies

Knowledge And Skills:

Required:

• Progressive experience building GenAI, RAG, and Agentic AI solutions, including prompt engineering, RAG pipeline design, and agent orchestration frameworks
• Hands-on experience with AWS Bedrock and related AI/ML services
• Strong programming skills in Python and Bash for automation, scripting, AI/ML tooling, and API development
• Advanced proficiency in Cloud infrastructure provisioning tools, specifically Terraform, including module development and state management
• Progressive experience using core AWS services to build and support cloud solutions leveraging architecture best practices (EC2, S3, Lambda, VPC, IAM, RDS, Systems Manager)
• Strong proficiency in CI/CD and deployment automation using GitLab pipelines
• Proficiency in React for frontend development of internal tools and administrative interfaces
• Strong understanding of version control systems (Git), branching strategies, and collaborative development workflows
• Experience with SQL and NoSQL databases, data modeling, and performance optimization

Nice to Have:

• Experience with vector databases, embedding models, and semantic search implementations
• Experience integrating advanced agentic frameworks (e.g., LangChain, LangGraph, or similar) into production systems
• Expertise in containerization technologies (Docker, ECS, EKS) and container orchestration
• Understanding of FinOps practices and cloud cost optimization
• Familiarity with security scanning tools and DevSecOps practices
• Experience with disaster recovery planning and implementation
• General familiarity with observability and monitoring practices (e.g., logging, metrics, tracing, alerting) and related tools such as CloudWatch, Grafana, or similar platforms

Qualifications:

• 3-5 years of relevant work experience in AI/ML engineering, cloud infrastructure, DevOps, or platform engineering
• Minimum bachelor's degree in computer science, Information Technology, Engineering
• Certifications related to Information Technology or AI/ML strongly preferred:
  1. AWS Certified Solutions Architect - Associate or Professional
  2. AWS Certified Machine Learning or AI Practitioner
  3. HashiCorp Certified: Terraform Associate or higher
  4. AWS Certified DevOps Engineer - Professional

Technical Competencies:

• Progressive knowledge of AI/ML system architecture, cloud computing concepts, microservices, and distributed systems
• Strong understanding of networking fundamentals, security principles, system design, and scalability considerations for AI workloads
• Advanced problem-solving skills with ability to debug complex technical issues across AI pipelines and multiple layers of the stack
• Ability to interpret and apply technical standards for programming and infrastructure design techniques
• Experience with Agile methodologies, sprint planning, and iterative development
• General awareness of performance measures, metrics, and system health indicators (nice to have)

Professional Competencies:

• Strong interpersonal, negotiation, creativity, and attention to detail skills
• Excellent oral and written communication skills tailored for the intended audience, including executives, business stakeholders, and technical teams
• Demonstrated ability to lead technical discussions and influence architecture decisions
• Proven track record of delivering AI/infrastructure projects on time and within scope
• Strong mentorship and knowledge-sharing abilities
• Understanding and application of risk management discipline in decision-making, particularly regarding responsible AI use
• Works under direction with infrequent checks; makes independent decisions based on established methods and policies

Additional Information:

• Hours:May require extended work hours for deployments, maintenance windows, or incident response
• Availability:May be subject to on-call rotation and callback as needed for production support
• Travel:Occasional travel including overnight stays may be necessary for training, conferences, or cross-site collaboration

The full salary range for the Engineer, Experienced job profile:

$94,600