About the role
About SnapLogic SnapLogic is the Agentic Integration Company, integrating AI, data, applications, and microservices into one powerful platform that transforms how enterprises connect, automate, and scale. Unlike legacy integration tools, SnapLogic is built for the AI era and trusted by global leaders, including AstraZeneca, Adobe, Verizon, Epsilon and Sony. With its industry-leading platform, SnapLogic empowers every team across the enterprise to securely build faster, smarter, AI-connected workflows – all through natural language and intuitive low-code design. Join the Agentic Integration movement at snaplogic.com .
The Role: We are looking for a Software Engineer to join our Agent Creator team, focusing on building and maintaining LLM integrations within the SnapLogic integration platform. In this role, you will design and implement AI-related Snap Packs that connect SnapLogic pipelines to diverse AI models, multimodal platforms, and evolving AI toolchains — enabling customers to build intelligent, enterprise-grade automation workflows at scale. You will own the full engineering lifecycle—from system design and prototyping through production deployment and operational excellence. Additionally, you will be a core driver of AI-assisted development practices within
the team, combining your expertise with advanced AI coding agents to accelerate product delivery. \n
What You'll Do: 1. Core Product & Integration Development AI Provider Integrations: Design, build, test, and ship Snap Packs for major AI providers, ensuring robust and high-performing connections. Cross-Provider Feature Parity: Implement and standardize advanced LLM capabilities across different providers, including Structured Outputs, Reasoning Models, Function Calling, Background Mode, and Vector Store integrations. Agent Framework & MCP: Develop and maintain the SnapLogic Agent Framework to support complex agentic workflows (incorporating iteration control, parallel tool calls, and observable execution via Agent Visualizer). Contribute to the Model Context Protocol (MCP) Server platform, including lifecycle management, observability, and registry. 2. Engineering Excellence & AI-Assisted Development AI-Augmented Coding: Leverage AI coding agents to write well-crafted, testable, and maintainable code, while maintaining full ownership, deep understanding, and accountability for the AI-generated codebase. Internal AI Innovation: Lead internal AI-driven initiatives to accelerate team velocity; rapidly prototype, validate, and productionalize internal AI tools (e.g., building dedicated AI Agents to automate Snap development). Code Quality & Operations: Write clean, structured, and testable Java/Python code adhering to checkstyle standards, maintaining a 90%+ unit test coverage target. Participate in code reviews and collaborate with QA/Release teams to validate builds across the production environment. 3. Strategy & Knowledge Sharing Trend Adoption: Stay at the forefront of the rapidly evolving AI ecosystem, selectively landing cutting-edge capabilities into the SnapLogic product line to deliver immediate customer value. Evangelism & Documentation: Institutionalize project learnings into high-quality technical documentation. Share knowledge through internal demos and evangelize engineering and AI best practices across the organization. What You'll Bring: Experience & Education: Bachelor’s degree with a minimum of 2 years of related experience, or an advanced degree, or equivalent practical work experience. Agentic & AI Patterns: Strong foundational understanding of agentic design patterns (tool use, agent loops, function calling, structured outputs, reasoning models). Frameworks & APIs: Robust understanding of MCP (Model Context Protocol) or AI agent orchestration frameworks. Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Google Vertex AI, or Amazon Bedrock; Anthropic experience is highly preferred). Backend & Data Skills: Solid experience building or consuming REST APIs and a strong command of JSON Schema and structured data validation. Engineering Persona: * Attention to Detail: Deep care for edge cases, comprehensive error handling, and intuitive user-facing validation/lint messages. Ambiguity Thriver: Ability to quickly self-learn, synthesize information, and drive towards a solution when facing ambiguous problems outside your immediate expertise. Collaboration: Strong cross-functional communication skills to work seamlessly across backend, platform, and UI teams.