AI Engineer

Overview

We have an immediate need for an Artificial Intelligence (AI) Engineer to support TO-005, Report Authoring and Dissemination (RAD). This role will work closely with system and software engineers to design, prototype, and integrate AI-driven capabilities into the existing RAD architecture—while also contributing to the design of next-generation architecture built for scalability and large data processing.

This is a transformative opportunity to build systems from the ground up that augment human intelligence, streamline workflows, and enable data-driven decision-making across enterprise environments handling high-volume, complex datasets.

Key Responsibilities

AI Solution Design & Development

• Lead end-to-end design and development of AI/ML solutions—from concept, prototyping, and architecture design to production deployment
• Write production-grade code and contribute to scalable, maintainable software systems
• Design modular, extensible architectures that support AI integration within enterprise platforms

Software Architecture & Engineering

• Contribute to or lead the design of enterprise-grade software architecture from scratch, including microservices and distributed systems
• Build backend services and APIs to support AI-driven applications and data pipelines
• Ensure systems are designed for scalability, fault tolerance, and high availability
• Implement best practices in software engineering, version control, CI/CD, and testing frameworks

Data Engineering & Large-Scale Processing

• Design and implement data pipelines to ingest, process, and analyze large structured and unstructured datasets
• Perform Exploratory Data Analysis (EDA) to inform model design and data strategy
• Optimize data storage and retrieval for performance and scalability

Model Development & Deployment

• Develop, train, evaluate, and fine-tune machine learning and deep learning models
• Implement robust validation, testing, and monitoring to ensure model accuracy, fairness, and reliability
• Deploy models into production environments using MLOps best practices

Collaboration & Communication

• Serve as a technical liaison across engineering, data, and mission stakeholders
• Clearly communicate AI approaches, tradeoffs, and system design decisions to both technical and non-technical audiences

Continuous Innovation

• Stay current with emerging AI/ML technologies, frameworks, and enterprise data solutions
• Identify opportunities to enhance system performance, automation, and intelligence capabilities

Requirements

Required Technical Skills

Programming Languages

• Strong proficiency in Python (primary for AI/ML development)
• Experience with one or more backend/system languages: Java, Go, C++, or Scala
• Familiarity with SQL and working knowledge of query optimization for large datasets

AI/ML Frameworks & Tools

• Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face
• Strong understanding of machine learning algorithms, deep learning, and data modeling techniques

Enterprise Software & Architecture

• Experience designing or contributing to scalable software architectures, including:
• Microservices-based architecture
• Distributed systems and event-driven design
• Experience building and consuming RESTful APIs or gRPC services
• Familiarity with containerization (Docker) and orchestration tools like Kubernetes
• Experience implementing CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions, etc.)

Data Engineering & Big Data Technologies

• Experience working with large-scale datasets and distributed processing frameworks such as:
• Apache Spark, Hadoop, or Flink
• Familiarity with data streaming technologies (Kafka, Kinesis)
• Experience with databases:
• Relational: PostgreSQL, MySQL
• NoSQL: MongoDB, Elasticsearch, DynamoDB

Cloud & MLOps

• Hands-on experience with Amazon Web Services (AWS) (e.g., S3, EC2, Lambda, SageMaker)
• Experience with MLOps tools for model deployment, monitoring, and lifecycle management
• Understanding of infrastructure-as-code (Terraform, CloudFormation) is a plus

Preferred Qualifications

• Experience building AI-enabled systems from the ground up in enterprise environments
• Familiarity with data governance, security, and compliance in large-scale systems
• Experience optimizing systems for performance, scalability, and cost efficiency
• Exposure to natural language processing (NLP), especially in document or report generation systems
• Experience supporting intelligence, analytics, or mission-focused platforms

Benefits

InterImage is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. InterImage provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.