• Design and implement modern AI architectures • Deploy machine learning models reliably into real-world applications • Create high-performance development environments and integrate AI workloads into existing system landscapes • Work closely with our Data Scientists and engineering teams • Understand requirements and translate them into robust technical solutions • Ensure our systems run with high performance, stability, and efficiency • Continuously evolve and improve them • Take responsibility for code quality and help advance our AI platform

About the Team The AI Center of Excellence team includes Data Scientists and AI Engineers that work together to conduct research, build prototypes, design features and build production AI components and systems. Our mission is to leverage the best available technology to protect our customers' attack surfaces. We partner closely with Detection and Response teams, including our MDR service, to leverage AI/ML for enhanced customer security and threat detection. We operate with a creative, iterative approach, building on 20+ years of threat analysis and a growing patent portfolio. We foster a collaborative environment, sharing knowledge, developing internal learning, and encouraging research publication. If you're passionate about AI and want to make a major impact in a fast-paced, innovative environment, this is your opportunity. The technologies we use include:• Python is used for analysis and modelling, with numpy, pandas, and scientific computing libraries.• Jupyter notebooks are used for local and remote analysis.• scikit-learn is used for machine learning.• Anomaly detection is used for large-scale unlabeled data analysis.• LLM/GenAI toolchains, including HuggingFace, Transformers, LangChain, CrewAI, and Agentic architectures, are used.• The AWS cloud ecosystem, including SageMaker, Bedrock, Lambda, EKS, and S3, is used.• Agentic AI platforms, including multi-agent orchestration, tool use, reasoning frameworks, and LLMOps, are used.• EKS is used for application deployment.• Terraform is used for infrastructure as code. About the Role Rapid7 is seeking a Staff AI Engineer to join our Data Science team as we expand and evolve our growing AI and MLOps efforts. You should have a strong foundation in software engineering and applied R&D in one of the key areas we focus on - traditional machine learning, neural networks, or generative AI. In this intersectional role, you will combine your expertise in AI/ML deployments, cloud systems and software engineering to enhance our product offerings and streamline our platform's functionalities. This role is ideal for someone who is:• Strong background in data science.• Proficient with AWS and ML/LLM infrastructure.• Excited about agentic AI, autonomous workflows, tool-augmented LLM systems, and building the future of AI-driven security. In this role, you will:• Work with security teams to define, scope, and design research efforts for new threat detections, automations, and AI-driven workflows.• Collaborate with data scientists to transform research into production-ready solutions, mentoring on both methods and execution.• Research, build, and evaluate ML and generative/LLM models, including agentic and multi-step reasoning systems.• Design and optimise agentic architectures, including tool-calling, decision-making, memory, orchestration, and evaluation frameworks.• Partner with engineering teams to ship AI features, integrating models into high-scale systems.• Deploy AI/ML workloads in AWS using SageMaker, Bedrock, Lambda, EKS, Step Functions, and related services.• Contribute to our LLMOps and MLOps workflows, improving evaluation pipelines, observability, reproducibility, and governance.• Support development of AI security features, improving reasoning, context understanding, automation, and analyst workflows.• Embrace agile development, iterative experimentation, and collaborative problem solving.• Mentor junior team members and uplift the technical bar for agentic AI and ML engineering. The skills you'll bring include: Core• 8-12 years of experience as a Data Scientist, ML Engineer, or AI Engineer.• Strong end-to-end practical expertise in ML/AI/DS.• Able to explore, experiment, and deliver independently. Proficiency in:• scikit-learn is used for classical machine learning.• PyTorch, TensorFlow, and Keras are used for deep learning.• HuggingFace, LangChain, and Transformers are especially useful for LLMs.• Pandas and NumPy are used for data preparation.• A clear understanding of modelling approaches and their suitability for different problems is necessary.• Strong communication skills and the ability to present technical concepts to diverse audiences are important.• The ability to collaborate across engineering, data science, product, and security teams is necessary.• Experience mentoring and guiding junior data scientists is preferred.• Agentic AI and LLM expertise is highly preferred.• Hands-on experience with agentic AI architectures, such as CrewAI, LangGraph, LangChain agents, tool-calling, and function-chaining, is preferred.• Experience building multi-step reasoning workflows, autonomous agents, or LLM-powered decision systems is preferred.• Understanding of prompt engineering, evaluation frameworks, LLM observability, and guardrails is preferred.• Experience working with AWS Bedrock, model selection, latency/cost trade-offs, and LLM deployment patterns is preferred.• AWS and cloud experience is highly preferred. Strong experience in AWS ML ecosystem:• SageMaker training & inference• Bedrock LLM integrations• Lambda for serverless workflows• EKS for containerized deployments• S3, Glue, Athena, IAM best practices• Experience with Terraform, IaC, and production deployment workflows Experience with the following would be advantageous:• Experience in the security industry• Deployment of AI and machine learning models• Implementing model risk management strategies, including model registries, concept/covariate drift monitoring, and hyperparameter tuning We know that the best ideas and solutions come from multi-dimensional teams. That's because these teams reflect a variety of backgrounds and professional experiences. If you are excited then please apply #LI-AK1 About Rapid7 At Rapid7, our vision is to create a secure digital world for our customers, our industry, and our communities. We do this by harnessing our collective expertise and passion to challenge what's possible and drive extraordinary impact. We're building a dynamic and collaborative workplace where new ideas are welcome. Protecting 11,000+ customers against bad actors and threats means we're continuing to push the envelope just like we' ve been doing for the past 20 years. If you 're ready to solve some of the toughest challenges in cybersecurity, we're ready to help you take command of your career. Join us.

• Partner with stakeholders across the organization to identify and prioritize high-value opportunities for AI and automation. • Design, develop, and support AI & automation systems that drive measurable business outcomes—from initial scoping to production deployment. • Design, build, and maintain scalable infrastructure, including frontend interfaces, backend services, and the underlying AI platform layer. • Create data pipelines and AI model context protocols, leveraging tools like MCP, LangChain, vector databases, and semantic search. • Ensure the high availability, performance, and security of AI platform services. • Contribute to platform growth by authoring SDKs, APIs, and comprehensive developer documentation. • Translate complex AI concepts for non-technical stakeholders and keep business goals front and center. • Keep pace with rapidly evolving AI models, frameworks, and research—and bring that knowledge back to the team.

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. WHY JOIN US If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! ABOUT THE ROLE As a Middle Backend Engineer, you’ll build the infrastructure that lets AI agents read, reason, and act on real energy data — connecting LLMs, APIs, and live data sources into production systems that run 24/7. High ownership, early stage, genuinely hard domain problem. If you want to build AI-native systems from the ground up with direct product impact, this is for you. WHAT YOU WILL DO - Build production backend systems connecting LLMs and coding agents with data and product APIs; - Design and deploy microservices using Python and optionally TypeScript; - Develop data connectors to external portals and public data sources; - Design backend infrastructure enabling AI agents to operate across data systems; - Ensure performance, scalability, and reliability of backend systems; - Implement observability and CI/CD pipelines for monitoring and maintenance; - Collaborate with cross-functional teams to translate business problems into technical solutions. MUST HAVES - 2+ years of experience building backend systems using Python and frameworks such as FastAPI; - Experience with Google Cloud Platform (GCP); - Experience owning backend services end-to-end (APIs, integrations, deployments, monitoring); - Strong skills in debugging and problem-solving; - Experience working with LLMs and AI tools (LangChain, OpenAI APIs, or similar); - Ability to rapidly prototype and iterate solutions; - Ability to work independently and manage priorities; - Strong communication skills across technical and business stakeholders; - Comfort working in fast-paced environments; - Upper-intermediate English level. NICE TO HAVES - Experience with Infrastructure as Code (Terraform); - Experience in energy, fintech, or automation domains; - Experience with AWS. PERKS AND BENEFITS - Professional growth: Mentorship, TechTalks, and personalized growth roadmaps. - Competitive compensation: USD-based pay with education, fitness, and team activity budgets. - Exciting projects: Modern solutions with Fortune 500 and top product companies. - Flextime: Flexible schedule with remote and office options.