Design and implement Go and TypeScript services, GraphQL APIs, and Kafka-based event pipelines for enterprise clients. Lead large-scale modernization efforts and ensure the reliability and observability of systems deployed on AWS and Kubernetes.
You will own the end-to-end lifecycle of the AI workflow infrastructure, ensuring it is secure, scalable, and reliable. You will also act as a DevOps leader to mentor teams and standardize practices for AI-driven automations across the company.
You will leverage AI tools to build and architect software features, design systems, and service layers for various client projects. Additionally, you will consult directly with clients, perform codebase audits, and coach client developers on industry best practices.
Design and implement durable distributed systems using Java, Temporal, and Kafka while managing Kubernetes-native infrastructure on AWS. Consult with enterprise clients to lead modernization efforts and build outcome-driven platforms.
Design and engineer scalable, secure AI-enabled automation workflows and orchestration patterns using n8n and Boomi. Establish enterprise standards for governance, monitoring, and responsible AI implementation to improve operational scale and productivity.
Translate complex business workflows into structured, implementation-ready requirements for AI-enabled automation and agentic workflows. Collaborate with engineers and architects to design scalable, governed solutions that reduce rework and accelerate business value.
Define and drive the enterprise architecture for AI automation and business transformation to reduce fragmentation and ensure scalability. Establish governance guardrails and architectural patterns for AI-enabled workflows, agents, and integration platforms.
Design and engineer scalable, secure AI-enabled automation solutions using n8n and Boomi to reduce manual work across the enterprise. Establish governance, development standards, and monitoring guardrails for AI agents and automated workflows.
Lead the design and engineering of scalable AI-powered automation solutions using n8n to improve organizational productivity and operational scale. Establish platform standards for development, monitoring, and governance while mentoring engineers on responsible AI and workflow engineering.
The engineer will own end-to-end delivery of AI-enabled products, designing and building features from UI to backend. They will implement complex AI workflows including RAG, agent systems, and guardrails while collaborating with strategists and clients.
Design and build the core architecture for an enterprise workflow automation platform while acting as the technical face of the company. Deploy solutions into customer environments to understand workflows and rapidly implement AI-enhanced automation.
