Overview

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.

Responsibilities

• Cybersecurity is seeking a Sr AI Engineer to join the Cyber Analytics and Data Science team. This position will use machine learning, data engineering, automation, and Data Science principles to solve enterprise problems and advance our Cybersecurity mission. This role is a key contributor to our practice and will be directly responsible for design, development, deployment, and automation.
• Structure business problems and drive viable, data-driven hypotheses in collaboration with business partners
• Ability to skillfully enumerate a business problem, quantify its impact, size relevant data, and document applicable sources
• Devise, develop and disseminate actionable intelligence from disparate data sources using advanced data analytics tools and techniques
• Ability to identify needs and opportunities for advancements in innovations, processes and automation
• Able to work proactively and take initiative without being specifically directed
• Ability to extract & aggregate data from disparate data sources
• Agentic AI Development: Design, build, and deploy agentic AI systems using frameworks such as LangChain, LangGraph, and related libraries.
• Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.
• RAG Pipelines: Implement and optimize RAG systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.
• LLM Engineering: Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation. Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.
• Enterprise AI Platform: Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.
• Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.
• MLOps & Observability: Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.
• Ability to perform in depth data analysis including but not limited to
• Machine Learning
• Classification
• Optimization
• Time Series analysis
• Pattern Recognition
• Establish and develop end-to-end automated processes (i.e.: data analyses, model development & implementation, manual processes, etc)
• Ability to communicate complex topics in an easy-to-understand manner when presenting to management
• Ability to visualize data and intelligence in easy-to-understand story telling

Qualifications

• 5 years overall experience in software development, data science, or machine learning.
• 1 year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.
• Strong programming skills in Python and basics in SQL.
• Expertise with LLM/SLM APIs, embeddings, and RAG systems.
• Familiarity with agentic AI protocols and exposure to Agent Development Kits (ADKs).
• Prior exposure to LangGraph, AutoGen, or related orchestration frameworks.
• 1 year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.
• Good communication, stakeholder management and good aptitude, attitude to be flexible.
• 2 or more years’ experience with developing Robotic Process Automation and/or automation efforts
• 2 or more years using Azure OR AWS cloud services
• 2 or more years skilled at data visualization (Tableau, PowerBI, etc.)
• 2 or more years with modern data engineering with APIs
• 2 or more years applying agile SDLC
• Contributions to open-source AI/ML projects are a plus.