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 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 first 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. #J-18808-Ljbffr