• Develop, train, and deploy machine learning models for predictive analytics, classification, and clustering. • Implement AI-based solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn. • Work with cloud platforms including AWS (SageMaker, Lambda, S3), Azure, and Google Cloud (Vertex AI). • Integrate and fine-tune Hugging Face transformer models (e.g., BERT, GPT) for NLP tasks such as text classification, summarization, and sentiment analysis. • Develop AI automation solutions, including chatbot implementations using Microsoft Teams and Azure AI. • Work with big data technologies such as Apache Spark and Snowflake for large-scale data processing and analytics. • Design and optimize ETL pipelines for data quality management, transformation, and validation. • Utilize SQL, MySQL, PostgreSQL, and MongoDB for database management and query optimization. • Create interactive data visualizations using Tableau and Power BI to drive business insights. • Work with Large Language Models (LLMs) for AI-driven applications, including fine-tuning, training, and deploying models for conversational AI, text generation, and summarization. • Develop and implement Agentic AI systems, enabling autonomous decision-making AI agents that can adapt, learn, and optimize tasks in real-time.

• Serve as the primary AI engineering partner to the CEO and executive leadership team, translating ideas, strategic questions, and emerging concepts into production-ready AI agents and workflows with minimal oversight. • Independently take ideas from concept to production, shaping problem statements, designing system architecture, implementing code, validating outputs, and operationalizing solutions without requiring heavy product or engineering management. • Design and implement complex, multi-step agentic workflows, including multi-agent orchestration, retrieval-augmented generation (RAG), tool use, memory strategies, evaluation frameworks, and cross-system automation. • Develop production-grade AI systems using modern LLMs, orchestration frameworks, and internal tooling, with strong attention to scalability, performance, observability, and clean engineering practices. • Operationalize AI responsibly by implementing guardrails, structured evaluations, monitoring, and validation layers to ensure predictable behavior, reliability, and compliance. • Partner closely with Security and Legal to properly gate sensitive use cases, implementing access controls, audit logging, data minimization, and enterprise-grade governance patterns while balancing safety and speed. • Translate ambiguous, high-visibility problems into clear technical solutions, balancing speed, quality, and risk while maintaining a high bar for accuracy and trust. • Evaluate, select, and rationalize AI tools and platforms, contributing to capability-to-tool decisions and ensuring consolidation, security alignment, and long-term sustainability across the enterprise. • Support post-launch adoption and iteration, incorporating feedback, refining workflows, and continuously improving performance, usability, and measurable impact. • Contribute to org-wide AI maturity by documenting architectural patterns, sharing best practices, and establishing repeatable approaches that elevate internal AI capabilities across Webflow.

Agentic AI Architect Why Us NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence. With two decades of experience guiding clients to realize the full potential of the ServiceNow AI Platform, we are one of the largest pure-play ServiceNow partners, uniquely focused on enabling enterprises to adopt AI they trust—AI that delivers lasting business value. We #GoBeyondWorkflows to create new kinds of experiences for our customers. Come join our Crew! The Role We are hiring an AI/ML Architect to join our team, in support of a large global client! You will be responsible for developing, deploying, and maintaining AI and machine learning models. Your expertise in Python, cloud services, databases, and big data technologies will be instrumental in creating scalable and efficient AI applications. We are #GoingBeyond Come join our crew! What You Will Be Doing - Develop, train, and deploy machine learning models for predictive analytics, classification, and clustering. - Implement AI-based solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn. - Work with cloud platforms including AWS (SageMaker, Lambda, S3), Azure, and Google Cloud (Vertex AI). - Integrate and fine-tune Hugging Face transformer models (e.g., BERT, GPT) for NLP tasks such as text classification, summarization, and sentiment analysis. - Develop AI automation solutions, including chatbot implementations using Microsoft Teams and Azure AI. - Work with big data technologies such as Apache Spark and Snowflake for large-scale data processing and analytics. - Design and optimize ETL pipelines for data quality management, transformation, and validation. - Utilize SQL, MySQL, PostgreSQL, and MongoDB for database management and query optimization. - Create interactive data visualizations using Tableau and Power BI to drive business insights. - Work with Large Language Models (LLMs) for AI-driven applications, including fine-tuning, training, and deploying model for conversational AI, text generation, and summarization. - Develop and implement Agentic AI systems, enabling autonomous decision-making AI agents that can adapt, learn, and optimize tasks in real-time. May perform additional duties as assigned. What You Bring Along - 7+ years of experience applying AI to practical uses. - Strong coding expertise in Python & SQL, with ML frameworks (TensorFlow, PyTorch, Scikit-learn). - Deep knowledge of algorithms, OOP, and functional design principles. - Proficiency with Pandas, NumPy, Matplotlib, and Seaborn. - Hands-on experience with cloud platforms such as AWS, Azure, and Google Cloud. - Experience with big data processing using Apache Spark and Snowflake. - NLP expertise with Hugging Face and cloud AI services - Strong understanding of database management, query optimization, and data warehousing. - Experience with data visualization tools such as Tableau and Power BI. - Ability to work in a collaborative environment and adapt to new AI technologies. - Strong analytical and problem solving skills. Education: - Bachelor’s degree in Computer Science, Data Science, AI/ML, or a related field. We Take Care of Our People NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard.  We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.in@newrocket.com.

• Design and develop AI Agents leveraging modern frameworks such as LangGraph and Model Context Protocol (MCP) to support SAP use cases. • Build and enhance the AI Agent experience layer using tools such as CopilotKit, Vercel AI SDK, or equivalent frameworks. • Enable and support cloud infrastructure (AWS or Azure) for AI Agent deployment, scalability, and secure operations. • Develop AI coding assets and MCP-based integrations to support the AI SDLC for SAP, including tooling and automation frameworks. • Design and implement SAP integrations using OData services, Function Modules, and CDS views. • Collaborate with SAP Basis teams to support system connectivity, transports, performance, and access management. • Work with SAP data structures to enable accurate context retrieval, analysis, and automation. • Integrate AI solutions with SAP incident and ticketing processes (e.g., ServiceNow) to support diagnostics, triage, and resolution workflows. • Partner closely with Technical Product Managers, SAP functional teams, and Managed Services stakeholders to deliver production-ready AI solutions.