Senior Software Engineer (AI/ML)

540•Arlington, VA

9h•Onsite

About The Position

540 is seeking a Senior Software Engineer (AI/ML) to support our partnership with Google and the Department of War in advancing mission-critical capabilities for a global data processing platform. This platform leverages Machine Learning, modern cloud and containerized technologies to ingest, process, and analyze high-volume, time-series data. The system leverages cloud-native infrastructure, while incorporating AI/ML capabilities to enhance signal analysis, anomaly detection, and data-driven insights. Engineers on this team build and scale full-stack features across user interfaces, backend services, and data pipelines that power mission-critical analytics. You’ll play a key role in integrating AI/ML-driven capabilities into production systems, enabling faster, more accurate operational decision-making. Location: Patrick SFB, FL or Arlington, VA. Candidates should be local to either location. Onsite support may be required based on mission and customer needs. Travel up to 25% Citizenship & Clearance Requirement: Per client requirements, candidates must be U.S. Citizens with an active DoW clearance with TS/SCI eligibility Education Requirement: Bachelor's Degree in Computer Science or related field (preferred) 540 Internal Thrive Level: Senior Software Engineer

Requirements

8+ years of professional software development experience
Experience developing microservices in containerized environments
Experience with, or a strong conceptual understanding of, LLM-based applications, RAG pipelines, and AI-driven decision systems
Experience with Python
Experience working with relational databases and data warehouses
Experience integrating AI/ML capabilities into applications (e.g., working with model inference APIs, ML pipelines, or data-driven features)
Ability to produce technical design documentation (system diagrams, architecture artifacts)
Familiarity with MLOps concepts (model deployment, monitoring, versioning)
Ability to design with future scalability and platform evolution in mind
Demonstrated ownership and ability to drive work from concept to production
Strong problem-solving skills and ability to navigate ambiguity
Excellent communication skills, including working directly with stakeholders or clients

Nice To Haves

Experience with Google Cloud Platform (GCP) or similar cloud environments
Experience designing and consuming RESTful APIs
Experience with API gateways and API management platforms, such as Google Apigee
Familiarity with API authentication and authorization (PKI, OAuth2, JWT, LDAP, SAML, etc.)
Experience working on U.S. Federal Government programs, particularly DoW environments
Google Cloud Professional-level certifications

Responsibilities

Design and develop machine learning models and applications for deployment to cloud-native services
Collaborate with data engineers and data scientists to productionize machine learning models and data pipelines
Collaborate with a cross-functional team of architects, engineers, and scientists to design and deploy Machine Learning Operations (MLOps) at scale
Integrate AI/ML capabilities into production systems (e.g., model inference APIs, decision-support features, anomaly detection workflows)
Design and optimize data models and persistence layers to support both transactional and analytical workloads
Enable intelligent application behavior by delivering AI and ML features to user-facing applications
Contribute to technical design documentation and system architecture artifacts
Lead or participate in code reviews, testing, and troubleshooting to ensure high-quality software
Drive system reliability through robust testing
Improve system performance, scalability, and reliability as the platform evolves