AI Engineer Job Reston area,Virginia USA,Software Development

AI Engineer -- Rapid Innovation Team

Help Build the Future of AI for Mission-Critical Organizations

Tech Trend is looking for a passionate AI Engineer to join our Rapid Innovation Team—a highly collaborative group focused on designing, prototyping, and delivering next-generation AI solutions for enterprise and U.S. Government customers.

This isn't a traditional software engineering role. You'll have the opportunity to explore emerging AI technologies, build innovative prototypes, and transform ideas into production-ready solutions that solve real-world business challenges. Working alongside cloud architects, software engineers, and AI specialists, you'll help shape the future of AI across multiple customer environments.

If you're excited about Generative AI, LLMs, AI agents, cloud-native machine learning, and rapid experimentation, we'd love to talk.

Before You Apply

U.S. Citizenship is required for this position due to federal customer requirements.
This position is based in Reston, VA and follows a hybrid work schedule.

What You'll Do

Design, develop, and deploy innovative AI solutions using Google Cloud Platform (GCP), with a focus on Vertex AI, Gemini, Document AI, Big Query ML, and other cloud-native AI services.
Lead rapid prototyping efforts to evaluate emerging AI technologies and demonstrate innovative solutions that deliver measurable business value.
Architect scalable AI and machine learning solutions from concept through production, including data pipelines, model training, deployment, monitoring, and continuous improvement.
Build Generative AI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt engineering, and modern orchestration frameworks.
Collaborate with business stakeholders, product owners, and engineering teams to translate complex business challenges into practical AI solutions.
Develop intelligent copilots, workflow automation, and AI-powered decision support tools for mission-critical customer environments.
Implement MLOps and Dev Ops best practices using Infrastructure as Code (IaC), Docker, Kubernetes/GKE, and automated CI/CD pipelines.
Design secure, scalable, and responsible AI solutions that meet government security and compliance requirements.
Mentor fellow engineers, contribute to architectural decisions, and help establish AI best practices across the organization.
Stay current with the rapidly evolving AI landscape and help evaluate new tools, frameworks, and technologies that can benefit our customers.

Technologies You'll Work With

Google Cloud Platform (Vertex AI, Gemini, Big Query ML, Document AI)
Python
Lang Chain & Lang Graph
Tensor Flow, PyTorch, scikit-learn
Vector Databases & Retrieval-Augmented Generation (RAG)
Docker & Kubernetes (GKE)
REST APIs & gRPC
Git, CI/CD, Infrastructure as Code
Azure OpenAI & Azure AI Services (preferred)
Modern Generative AI and Agentic AI frameworks

Required Qualifications

Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical discipline.
5 years of software engineering experience with at least 3 years designing and delivering AI or machine learning solutions.
Strong Python development experience and familiarity with AI/ML frameworks such as Tensor Flow, PyTorch, scikit-learn, Lang Chain, or similar technologies.
Hands‑on experience building AI solutions on Google Cloud Platform, including Vertex AI and related GCP AI services.
Experience designing scalable machine learning systems from experimentation through production deployment.
Experience with containerization and cloud‑native deployment using Docker and Kubernetes.
Familiarity with vector databases, embeddings, prompt engineering, and Retrieval-Augmented Generation (RAG).
Experience developing APIs and integrating AI services into enterprise applications.
Strong communication skills with the ability to collaborate across technical and business teams.
Demonstrated technical leadership through architecture ownership, mentoring, or leading engineering initiatives.

Preferred Qualifications

Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification.
Experi…