• Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. • Lead innovation efforts around cutting-edge AI, owning the architecture and strategy for fine-tuning and Retrieval-Augmented Generation (RAG). • Guide the development of high-impact prototypes and oversee the evolution of scalable LLM pipelines. • Ensure robust governance, security, and performance across all model implementations. • Provide technical leadership, evaluate emerging LLM technologies, set best practices, and help drive transformation through effective deployment of generative AI.

• Connect to client systems — databases, APIs, CRMs, and other SaaS tools — and get data reliably out of and into them. • Extract, clean, transform, and move data so it is structured and usable by AI features, including retrieval and agentic workflows. • Build and maintain data pipelines that feed the Applied AI Engineer’s RAG and agent systems with current, correct data. • Use AI coding tools to accelerate integration work, while applying real engineering judgment to the bespoke, messy parts those tools handle poorly. • Handle the practical realities of client data: undocumented schemas, inconsistent formats, partial records, and access constraints. • Apply data-handling, security, and privacy best practices throughout, especially with client data. • Collaborate with the Builder and the Applied AI Engineer to ensure data flows cleanly end to end, and document integrations and pipelines in Notion so they are repeatable and maintainable.

Role Description We are seeking a Senior Data Integrations Engineer - AI with expertise in Enterprise System Integrations, Business Process Automation, and AI technologies. In this role, you will design, build, and deploy scalable integration solutions and automations, as well as develop AI Agents using various technologies across multiple domains. The Global Technology Operations team is dedicated to digitally transforming and scaling Celigo's business, enhancing productivity, and improving operational efficiency. As an AI Integrations Engineer, you will support the business by seamlessly connecting systems and data. Additionally, you will build automations using integrator.io and AI concepts to eliminate redundant tasks, enabling teams to focus on higher-value activities. - Champion the Celigo product through transformational integrations that enable scalable business growth. - Build AI agents/integrations using Celigo’s integrator.io and frameworks like LangChain and LangGraph, and using best practices in AI SDLC. - Be an advocate for Celigo and show the art of the possible with AI for different stakeholders within Celigo and to Celigo customers/partners/builders. - Design, build, and deliver scalable data pipelines leveraging modern cloud architectures. - Collaborate with business process experts to develop solutions for complex systems and data platforms that drive revenue growth. - Ensure your integrations adhere to engineering best practices, emphasizing data quality, accuracy, operability, and security. - Build and maintain trusted relationships with technical and business teams. - Manage multiple projects concurrently, including operational tasks. - Serve as the owner and final escalation point for your integrations. - Produce clear, accurate technical documentation, develop support processes and procedures, and facilitate smooth hand-offs to peers and other organizational units. Qualifications - Proven ability to interface with diverse stakeholders across business units and levels, gather requirements, and manage follow-ups. - Demonstrated track record of delivering projects end-to-end with strong accountability. - Thinks like an owner—takes full charge of projects from inception to delivery while keeping Celigo’s best interests in mind. - Willingness to work flexible hours to collaborate with India stakeholders effectively. - Excellent written communication skills; experience with data visualization (graphs and plots) is a significant advantage. - Able to quickly learn business processes, understand requirements, and communicate designs that address both technical and business challenges. - Basic knowledge of SQL, Snowflake stored procedures, AWS S3, along with a clear understanding of integration design patterns. - Basic knowledge of Agent SDKs and Model context protocol. - Familiar with various authentication mechanisms such as OAuth 2.0, SAML2, and JWT Bearer Tokens. Requirements - A BS/BA in Information Systems, Computer Science, or equivalent practical experience is preferred. - Strong expertise in developing integrations using REST and SOAP APIs, with at least 5+ years of experience in JSON and XML schema design. (must have) - 1+ years of experience in building AI solutions using RAG, LangGraph, Web scraping, or any other AI technology. - Proficient in JavaScript/Python for data processing within integration projects. - Good to have experience in developing AI agents or bots that autonomously interact with various tools and systems to derive and act upon business insights. - Good to have experience in integrating Large Language Models (LLMs) such as OpenAI's GPT series, Google's Gemini, or Anthropic's Claude with external APIs, vector databases, and enterprise platforms to automate workflows and enhance decision-making processes. - Solid understanding of prompt engineering, context management, and the orchestration of multi-step tasks using AI-driven solutions. - Knowledge of system and software engineering architecture principles and best practices is a plus. - Experience supporting business teams and a strong grasp of processes like Quote-to-Cash, Procure-to-Pay, Lead-to-Opportunity, and Hire-to-Retire. - Hands-on experience with cloud applications like Salesforce, HubSpot, NetSuite, Zendesk, Gong, Gainsight, and similar platforms. - Experience in designing and building integration solutions, ideally within Sales or Customer Success domains. Benefits - Three weeks of vacation (starting year one) - Wellness days and holidays to recharge - Parental leave and a generous benefits package - Monthly tech stipend - Recognition and career development opportunities

• This is a senior-level role focused on the design, development, and ownership of data solutions built primarily on Snowflake Data Cloud. • You will lead the architecture and implementation of scalable data pipelines, establish robust data models, and enforce data governance and security standards across the platform. • Design, build, and own scalable data pipelines and ingestion processes using SQL, Python, dbt, and cloud-native tools. • Architect and implement ELT/ETL patterns across batch, incremental, and CDC pipelines. • Lead the development of data models using Dimensional Modeling, Data Vault, or Lakehouse approaches. • Own the design and optimization of Snowflake environments, including warehouse sizing, cost governance, storage standards, schema management, and performance tuning. • Work with cloud platforms (AWS, Azure, or GCP) to integrate with Snowflake and deliver high-performance, cost-efficient solutions. • Lead pipeline orchestration using Airflow, dbt Cloud, or similar tools. • Establish and enforce data governance frameworks, access controls, and security protocols with particular focus on Snowflake-native capabilities such as row-level security, dynamic data masking, and data sharing. • Define and maintain data quality standards, lineage documentation, and compliance requirements.