Job
Description
About Boomi And What Makes Us Special
Are you ready to work at a fast-growing company where you can make a difference? Boomi aims to make the world a better place by connecting everyone to everything, anywhere Our award-winning, intelligent integration and automation platform helps organizations power the future of business At Boomi, youll work with world-class people and industry-leading technology We hire trailblazers with an entrepreneurial spirit who can solve challenging problems, make a real impact, and want to be part of building something big If this sounds like a good fit for you, check out or visit our Boomi Careers page to learn more Join Boomis Enterprise AI Team Where Innovation Meets Impact Boomis Enterprise AI Team drives the creation of intelligent systems that augment business operations and customer experiences through AI-driven automation As a Lead Forward Deployed Engineer, youll be the driving force behind the creation of cutting-edge internal AI platforms and agentsour Customer Zero prototypes that bring new AI capabilities to life before they reach the world In this role, you will: Architect and deploy next-generation AI systems that blend automation, reasoning, and adaptability Collaborate across R&D, platform engineering, and product teams to turn bold ideas into scalable realities Experiment and innovate, pushing the boundaries of multi-agent collaboration, context-aware retrieval, and autonomous reasoning Serve as a trailblazer for AI-first development, influencing the roadmap of Boomis future products and intelligent infrastructure If you thrive at the intersection of engineering excellence, applied AI, and creative problem-solving, this is your chance to shape the future of intelligent business automationstarting from the inside out Be bold Build smarter Lead the AI revolution at Boomi Key Responsibilities AI Agent Design & Engineering: Architect, build, and orchestrate intelligent agents using ChatB, Agent Studio, and LLM frameworks (eg OpenAI, Anthropic, Claude, Gemini) Internal Platform Innovation (Customer Zero): Lead the design, experimentation, and validation of new AI workflows that drive measurable internal productivity improvements Multi-Agent Systems: Design agent hierarchies and orchestration pipelines using coordination frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel) Applied Research: Investigate and integrate state-of-the-art AI techniques (tool use, reasoning, memory, reflection, RAG, and function calling) Integration Engineering: Build APIs and connectors enabling agents to interact with Boomis integration and automation ecosystem System Architecture & Performance: Ensure that deployed agents meet enterprise standards for security, observability, and scalability Knowledge Graphs & Retrieval: Implement vector databases, knowledge graphs, and retrieval pipelines to enhance context-aware responses Evaluation & Metrics: Define KPIs, monitor LLM behaviors, and evaluate model performance through offline and live testing Collaboration & Enablement: Work with platform, data, and UX teams to deliver integrated AI services and assist internal users with adoption and best practices Documentation & Standardization: Develop reusable frameworks, templates, and design patterns for internal AI applications Ethics & Governance: Support internal guidelines for AI transparency, data governance, and model safety within enterprise deployments Tooling & MLOps Integration: Integrate pipelines with LLMOps, CI/CD, and API gateways for repeatable deployment Mentorship & Evangelism: Mentor internal teams on AI agent architectures, experimental methods, and technical excellence Essential Skills & Qualifications Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or Software Engineering (RQF Level 6+) Advanced coding skills in Python, TypeScript, or JavaScript Experience with LLM-based development, RAG pipelines, and agent orchestration frameworks Deep understanding of API design, microservices, and event-driven architectures Familiarity with machine learning frameworks (PyTorch, TensorFlow, Hugging Face) Experience working with vector databases (Pinecone, Weaviate, Chroma, FAISS) and retrieval systems Knowledge of data pipelines and ETL tools, especially integration with the Boomi platform Exposure to AI ethics, model evaluation, and prompt optimization techniques Experience deploying workloads to cloud platforms (AWS, Azure, GCP) using modern DevOps and infrastructure-as-code practices Understanding of containerization (Docker, Kubernetes) for scalable AI deployments Excellent communication and stakeholder engagement skills, capable of bridging research and engineering domains Research-oriented mindset with a track record of innovation, rapid prototyping, and cross-functional collaboration
