Role overview
TechTrend is seeking a talented Senior AI Engineer to join our AI Rapid Innovation team. Using a modern technology stack and agile approach, in this role you will have the opportunity to lead the development and prototyping of cutting-edge AI solutions that transform how our clients leverage artificial intelligence in their operations.
Be a member of an environment that thrives on innovation and ideas of all members of the team. Our environment is highly collaborative and allows you the opportunity to continue building your skills through training and multiple diverse projects while mentoring and guiding technical team members.
What you'll work on
Lead the design, development, and prototyping of innovative AI solutions primarily using Google Cloud Platform (GCP) AI/ML services including Vertex AI, AI Platform, Document AI, and related technologies.
Partner with stakeholders, product teams, and technical leadership to rapidly solution and architect AI capabilities that address complex business challenges for major U.S. Government customers.
Provide technical leadership and mentorship to development team members, guiding best practices in AI/ML engineering, cloud architecture, and agile development methodologies.
Collaborate closely with business teams, data scientists, and IT professionals to translate business requirements into scalable, production-ready AI solutions.
Architect and implement end-to-end AI pipelines including data ingestion, model training, deployment, monitoring, and continuous improvement using GCP native services.
Develop proof-of-concepts and prototypes that demonstrate the art-of-the-possible with generative AI, large language models (LLMs), computer vision, natural language processing, and predictive analytics.
Leverage experience with Azure AI services (Azure OpenAI, Azure Machine Learning, Cognitive Services) to provide cross-cloud AI solutions when required.
Implement responsible AI practices including model explainability, bias detection, security controls, and compliance with industry standards and government regulations.
Work within DevOps/MLOps environments to automate infrastructure provisioning, model deployment, and monitoring using Infrastructure as Code (IaC) tools.
Create comprehensive technical documentation including architecture diagrams, API specifications, model cards, and operational runbooks for AI solutions.
Demonstrate a high degree of adaptability and willingness to take on varied responsibilities, often beyond the initial scope of the role, to meet evolving business needs and contribute to cross-functional initiatives.
Stay current with emerging AI technologies, tools, and best practices, and evangelize innovations within the team and to client stakeholders.
What we're looking for
Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification
Experience with Azure AI services (Azure OpenAI Service, Azure Cognitive Services)
Familiarity with generative AI platforms and frameworks (OpenAI API, Gemini, etc.)
Experience with data engineering tools and practices
Knowledge of AI security, model governance, and responsible AI practices