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

401K: up to 3% discretionary profit sharing contribution + 100% match on the 1st 7% of pay
PTO: 20 days per year
Healthcare, dental, vision, Free for a single participant
$50,000 Life insurance provided, additional voluntary life insurance available

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.

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