AI Engineer

Overview

We are seeking a dynamic and innovative AI Engineer to join our forward-thinking technology team. In this role, you will be at the forefront of developing cutting-edge artificial intelligence solutions that drive business insights and operational efficiencies. Your expertise will help shape the future of AI applications across diverse platforms, ensuring scalable, robust, and impactful models. This position offers an exciting opportunity to work with state-of-the-art tools and frameworks in a collaborative environment dedicated to technological excellence and innovation.

Duties

• Design, develop, and optimize AI models using frameworks such as TensorFlow and machine learning/AI-based analysis tools to solve complex business problems.
• Implement scalable machine learning solutions leveraging cloud services like AWS and machine learning cloud platforms for model training, deployment, and management.
• Conduct statistical modeling and analysis using tools such as SAS, R, and statistical analysis software to extract actionable insights from large datasets.
• Develop data pipelines with ETL processes, utilizing Talend, Bash (Unix shell), Hadoop, Spark, and other big data systems to prepare data for analysis.
• Collaborate with data engineers to design efficient SQL databases and database schemas that support high-performance data analytics.
• Apply natural language processing (NLP) techniques for text analysis and generative AI applications to enhance product features or customer engagement strategies.
• Evaluate AI models through rigorous model evaluation techniques, predictive modeling analysis, and scalability testing to ensure optimal performance across platforms.
• Deploy AI models into production environments with a focus on model deployment best practices, model monitoring, and continuous improvement cycles.
• Engage in data mining activities to uncover hidden patterns within large datasets using big data systems like Hadoop and Spark implementation.
• Contribute to research initiatives by applying statistical analysis for research purposes, advancing AI capabilities through innovative approaches such as quantum engineering or linked data integration.
• Build and integrate LLM-based features (RAG pipelines, chatbots/copilots, agentic workflows) into client applications
• Develop and maintain data pipelines for model training, fine-tuning, and evaluation
• Implement and tune ML models (classification, regression, NLP, or similar) as required by the use case
• Build evaluation harnesses to measure model accuracy, hallucination rate, latency, and other quality metrics
• Deploy and monitor models and AI features in production, including logging, alerting, and drift detection
• Implement AI-specific security guardrails: input/output filtering, prompt-injection defenses, and access controls
• Collaborate with the AI Architect on technical design decisions, platform selection, and architecture reviews
• Document technical implementation details to support federal compliance and ATO documentation requirements

Skills

• Proficiency in programming languages including Python, Java, C, R, VBA, and Bash (Unix shell).
• Extensive experience with machine learning frameworks such as TensorFlow, Spark MLlib, and other AI implementation tools.
• Strong knowledge of cloud-based machine learning services on AWS or similar platforms for scalable model training and deployment.
• Expertise in big data systems including Hadoop, Spark, SQL databases, and data analytics tools like Looker.
• Solid understanding of statistical analysis techniques for research purposes combined with statistical modeling skills.
• Familiarity with natural language processing (NLP), generative AI models, and predictive modeling analysis methods.
• Experience designing efficient database schemas and implementing ETL processes using Talend or similar tools.
• Knowledge of quantum engineering principles related to advanced AI research is a plus.
• Ability to work effectively in collaborative environments while managing multiple projects focused on AI/ML innovation.
• 3-6 years of software engineering or ML engineering experience, including hands-on generative AI/LLM project work
• Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent experience)
• Experience delivering to federal government clients preferred but not required
• Programming: Python (primary), with experience in relevant ML/AI libraries (Py…