Lead AI Engineer

Description

About the Company

Our core values of People Matter, Integrity, and a Commitment to Excellence drive all that we do. By joining us, you’ll become a part of a fun and diverse team of talented and creative consultants who share the goal of using the latest technology to solve business challenges. We provide our clients with a dynamic mix of services and deliver focused solutions like no one else.

We're seeking talented and bright team players who are passionate about technology and want to work in a fast-paced, dynamic, and ego-free culture while applying a creative approach to problem-solving. Team members who like to grow their skill sets while solving challenging, real world business problems thrive.

About the Role

We are seeking a Lead AI Engineer who is passionate about cutting-edge technology and thrives in a dynamic and collaborative environment. As part of our team, you will lead the development of innovative AI solutions while working with a diverse and talented group of engineers, subject matter experts and data scientists. We're looking for a well-rounded team member to contribute to digital transformation efforts in the US Army.

In this role, you will apply creative problem-solving to some of our most complex challenges, including automating and optimizing business processes through AI-driven platforms. You’ll spearhead the development and deployment of AI models, from deep learning and NLP to large language models (LLMs), across cloud platforms. Working closely with cross-functional teams, you will drive the automation of model deployment pipelines, standardize data processes, and deliver AI capabilities that unify and streamline operations. This is a unique opportunity to lead AI innovation in a culture that values creativity, collaboration, and continuous learning, while delivering impactful solutions to the Department of Defense.

RESPONSIBILITIES

AI Application Development:

• Design, build and deploy advanced machine intelligence applications such as digital agents (chatbots) and pattern recognition systems for text, image, and speech recognition.
• Develop and optimize Natural Language Processing (NLP) systems, with a focus on entity extraction and machine learning-driven language understanding.
• Deep Learning Model Development:
• Design and implement deep learning models for various AI applications, including text classification, image recognition, and generative models.
• Perform machine learning optimization via feature selection, metrics analysis, and hyperparameter adjustment for enhanced model accuracy and efficiency.

Large Language Models (LLM) & Retrieval-Augmented Generation (RAG):

• Apply expertise in large language models (LLM) and Retrieval-Augmented Generation (RAG) to create scalable, high-performance language models that drive business and product innovation.

Model Deployment & Real-Time Monitoring:

• Deploy machine learning models into larger systems, ensuring seamless integration and monitoring real-time performance. Implement feedback loops to continuously optimize models based on production data.

Platform Capability Development:

• Develop Generative AI & Traditional AI platform capabilities on enterprise on-prem and cloud platforms.
• Build automation capabilities for ML and LLM model deployment on on-prem and cloud platforms (e.g., GCP-Vertex AI, Azure ML).
• Standardize model consumption and data pipeline deployment, enabling multiple Lines of Business (LOB) to utilize the deployed models efficiently.

UI Development for AI Applications:

• Lead the design and development of intuitive and responsive user interfaces for AI applications, ensuring smooth user interaction and visualization of AI-driven insights.
• Work closely with UX/UI designers and front-end developers to create interfaces that enhance the user experience of AI-powered tools such as chatbots and AI dashboards.

Collaboration & Optimization:

• Collaborate with Data Scientists to optimize the scoring pipeline for AI models, ensuring high-performance scoring and inferencing capabilities for ML models and LLMs.
• Work with product owners, DevSecOps teams, data scientists, and support teams to define and drive end-to-end model scoring pipelines, ensuring seamless deployment and scalability.
• Design, build and deploy artificial intelligence solutions that empower humans to make more informed decisions.
• Participate in day-to-day standups to contribute to platform capability development and ensure alignment across teams.

Leadership & SME Guidance:

• Provide Subject Matter Expertise (SME) guidance to data science teams on software engineering principles, model tra