Job Description

Staff Software Engineer - AI


Rapid7 - Pune, India (Full-Time)


Rapid7 is looking for a talented and experienced Staff Software Engineer - AI to join our team in Pune. This role is pivotal in driving the adoption and implementation of cutting-edge Artificial Intelligence and Machine Learning technologies across our product suite, with a focus on enhancing security, detection, and automation capabilities. You will be responsible for the full lifecycle of AI/ML initiatives, from research and prototyping to production deployment and monitoring.


The Opportunity


As a Staff Software Engineer - AI, you'll be a technical leader, working with cross-functional teams to design, build, and scale our next generation of AI-powered security products. You'll set the technical direction for complex ML systems, mentor engineers, and ensure our AI solutions are robust, performant, and adhere to best practices for governance and responsible AI.

Key Responsibilities:

AI/ML System Architecture & Delivery: Lead the design and implementation of large-scale, production-grade AI/ML systems, including RAG Pipelines (Vector DBs), LLM applications, and advanced Deep Learning models. LLM & Generative AI: Drive the integration and LLM Orchestration (LangChain/LangGraph) of large language models for tasks like code analysis, threat summarization, and interactive security workflows. Core ML Development: Build and deploy various ML models, including Supervised ML (Classification/Regression), Unsupervised ML (Clustering/Anomaly Detection), and Deep Learning (NLP, CNN, RNN etc.) models, with a specific focus on Malware Detection models and Malware Behavior based Models. Data & Feature Engineering: Oversee Data Acquisition, cleaning, enrichment, Transformation and complex Feature Engineering necessary to power high-quality ML models. Model Quality & Trust: Implement rigorous processes for LLM Evaluation (Promptfoo/HELM) and quality assurance. Utilize tools like Model Explainability (SHAP, LIME) to ensure transparency and debug model behavior. Guardrails & Governance: Define and enforce Guardrails & Governance policies for AI systems to ensure safe, ethical, and compliant deployment. Optimization & Deployment: Optimize models and pipelines for performance and cost-efficiency. Utilize cloud services like AWS Bedrock/SageMaker/Lambda for robust, scalable MLOps. Explore techniques like Fine-tuning (LoRA/PEFT) for specialized model performance. Technical Leadership: Act as a subject matter expert, mentor junior and senior engineers, and champion engineering excellence within the AI domain.

Required Skills & Experience

7+ years of professional software engineering experience, with at least 4+ years focused on building and deploying production-grade AI/ML systems. Expert proficiency in Python and relevant ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Deep practical experience with LLM Orchestration, RAG Pipelines, and Vector Databases. Proven expertise in Deep Learning, specifically in NLP or advanced time-series/behavioral modeling (e.g., User Behavioral Models). Strong background in MLOps, CI/CD, and deploying models on cloud platforms, particularly AWS Bedrock/SageMaker. Experience with Prompt Engineering and implementing Guardrails for generative AI. Excellent communication, collaboration, and technical leadership skills.

Desirable Qualifications

Experience in the Cybersecurity domain or with large-scale behavioral data modeling. A Master's or PhD in Computer Science, Machine Learning, or a related quantitative field. Familiarity with advanced model evaluation tools like Promptfoo/HELM. Experience with model compression or fine-tuning techniques (LoRA/PEFT). * Published papers or active contributions to the ML community.