Professional Software/Data Scientist/Engineer

Overview

Geosyntec has an exciting opportunity for a Professional Software/Data Scientist/Engineer with an emphasis on Artificial Intelligence (AI) in our Kennesaw, GA office. This role leverages strong foundations in computer science and software engineering to design, build, and deliver data-intensive and AI-enabled systems that accelerate internal innovation and client-facing digital solutions.

About the role

The role blends modern software engineering, data engineering, and applied AI practices. You will partner with our engineering, research and development teams, provide best-in-class solutions, and ensure our digital tools remain cutting-edge. Candidates may come from software engineering, data science/engineering, or hybrid technical backgrounds, provided they have experience delivering production-grade systems in data-intensive or AI-enabled environments.

Responsibilities

• Design and lead AI-based/digital solutions and services, selecting optimal architectures aligned with the company’s cloud, data, and security standards.
• Translate business requirements into implementable architectures and solutions across data platforms, AI models, application services, orchestration frameworks, and extensibility layers.
• Design, develop, test, deploy, support and enhance new or off-the-shelf secure AI and ML models, including Retrieval-Augmented Generation (RAG), tailored to domain-specific deliverables and company initiatives.
• Build the Generative AI platforms, systems and infrastructure and apply general knowledge of software development and infrastructure as code practices.
• Automate engineering and business processes using scripting languages and modern automation platforms, including Python and cloud-based AI services from Microsoft (e.g., Copilot Studio, Azure Foundry, etc.).
• Design and implement user interfaces, data visualizations, and other interaction layers as needed to support AI-enabled workflows and decision-making.
• Develop Python scripts for data analysis and automation of engineering analysis.
• Design, develop, test, deploy, support, and enhance production-grade applications and services that enable AI and data-driven workflows.
• Integrate front-end components with back-end APIs and services for seamless data interactions.
• Ensure UI/UX best practices to improve user experience and workflow efficiency.
• Develop, manage, and maintain relational database applications for data storage and retrieval, ensuring performance, scalability, and security.
• Implement and maintain RESTful APIs and backend services to support frontend applications.
• Lead solution architecture for priority AI, generative AI, and agent-based use cases, including hands-on technical design, decision-making, and architecture reviews.
• Identify technical, security, data, and delivery risks associated with AI solutions and implement appropriate mitigation strategies.
• Embed Responsible AI principles into solution designs, including privacy, security, transparency, and model risk management.
• Maintain a strong awareness of the latest trends in AI/ML and their applications to engineering consulting and related industries, ensuring that the company remains at the forefront of technological advancements.
• Provide training and support to internal teams on AI/ML technologies and best practices, fostering a culture of continuous learning and innovation.
• Maintain comprehensive documentation for all AI/ML projects, including design specifications, solution diagrams, implementation plans, and user guides.

Qualifications

• At least 5 years (7+ preferred) of related work experience or equivalent combination of education and experience.
• Demonstrated experience in software engineering, working with large data sets, and developing end-to-end workflows in a professional environment.
• Proficiency in at least one modern programming language (for example, Python, C#, Java, or similar) and ability to write maintainable, testable code.
• Proven experience in developing and deploying AI/ML models, with a strong understanding of RAG models and their implementation using LLMs.
• Proficiency with vector stores, semantic search, and related technologies.
• Knowledge of fine-tuning techniques for LLMs to adapt them to specific tasks and domains.
• Familiarity with other AI and ML technologies such as reinforcement learning, computer vision, or recommendation systems.
• Experience with or ability to learn and work with Microsoft Azure services, Microsoft Foundry, Azure OpenAI, Copilot Studio, Power Platform, cognitive search, vector databases, and API integrations.
• Strong understanding of identity, networking, data governance, and security within cloud-based environments.
• Demonstrated ability to lead technical design discussions, manage stakeholders, and discuss with engineering teams.
• Strong communication skills and ability to translate needs between business stakeholders and technical teams.