AI Engineer

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.

Responsibilities

• 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.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or related technical field
• 5+ years of hands-on software development experience with demonstrated expertise in Python, and familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, or similar
• 2+ years of experience in a technical leadership or team lead capacity, including mentoring developers and guiding technical decisions
• Proven experience designing and deploying AI/ML solutions in Google Cloud Platform, with hands-on knowledge of Vertex AI, BigQuery ML, Document AI, or other GCP AI services
• Strong understanding of machine learning fundamentals, model development lifecycle, and production ML system design
• Experience with containerization (Docker, Kubernetes/GKE) and orchestration of AI workloads in cloud environments
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) architectures for generative AI applications
• Experience with API development and integration using REST, gRPC, or similar protocols
• Strong problem-solving skills with ability to rapidly prototype and iterate on AI solutions

Preferred Qualifications

• 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