HIGH BRIDGE CONSULTING LLC

Build and design composable workflow steps for an agentic workflow-orchestration platform integrating LLM and AI agent tool-use. | Senior-level TypeScript development with expertise in workflow orchestration engines, distributed systems, event-driven architecture, and Kubernetes deployment. | Our client, a 3rd-generation management consulting firm. They are now looking to add to their team and are hiring a Senior TypeScript Backend Engineer can be 100% remote Project Description Client is building an agentic workflow-orchestration platform in-house, starting with vulnerability discovery as its first workflow. The client's engineering team with two architect-level, hands-on TypeScript engineers plus a part-time solution-partner subject-matter expert, working the priorities the client sets rather than owning delivery of a fixed scope end to end. Keywords: Workflow/orchestration engines (Temporal, Dapr, AWS Step Functions) Distributed systems and event-driven architecture Kubernetes Senior TypeScript backend engineering Required (Must have) Tech lead or team lead level TypeScript development: writes production code hands-on as a lead, not solely reviewing architecture or delegating implementation. Direct experience building on workflow/orchestration engines such as Temporal, Dapr, or AWS Step Functions. Strong distributed-systems background: message queues/pub-sub (e.g. Kafka), event-driven architecture, and retry/idempotency patterns. Kubernetes or Red Hat OpenShift experience: deployment, scaling, and networking basics. Enterprise architecture background sufficient to work from a design document and exercise sound, independent judgment in a fast-moving environment where scope is still being designed and priorities may shift. Nice to have (ideal to have) Comfort evaluating and comparing infrastructure platforms and making build-vs-buy recommendations. Experience in regulated or financial-services environments: governance and audit-trail thinking. Integrate LLM/AI agent tool-use into platform workflows as directed by the client. Duties to be performed (Details around what the consultant would do on the project) Augment the client's engineering team building the agentic workflow-orchestration platform, per client direction and prioritization. Evaluate and recommend workflow/orchestration engine and infrastructure choices. Design and implement composable, polyglot workflow steps within the orchestration harness. Environment (Details around what technologies are used at the client) TypeScript Temporal or a comparable workflow orchestration engine Kubernetes or Red Hat OpenShift Kafka or a comparable message queue/pub-sub system Containerized, polyglot workflow steps This is a remote position.

Build and deploy multi-agent AI workflows and RAG systems in a secure cloud environment collaborating with architects and stakeholders. | Strong experience with Agentic AI systems using LangGraph and Python, and proven production-grade AI deployment in enterprise settings. | We are seeking a hands-on Senior AI / Data Engineer to build and deploy production-grade Agentic AI and multi-agent solutions for a major enterprise transformation. This role is focused on engineering and production deployment—not research or experimentation. What You Will Do Build and deploy multi-agent AI workflows using LangGraph or similar frameworks. Develop RAG, retrieval, validation, knowledge-mapping, and document-generation agents. Integrate enterprise-approved LLMs, including Anthropic Claude or comparable platforms. Implement human-in-the-loop workflows, checkpointing, and resumable agent processes. Build automated data reconciliation and validation pipelines. Work with structured and unstructured enterprise data in a secure cloud environment. Partner with solution architects and business stakeholders to productionize AI solutions. Required Skills Production experience building Agentic AI or Multi-Agent systems. Strong LangGraph or comparable agent orchestration experience. Hands-on experience with RAG, LLM integration, and enterprise AI applications. Experience with Databricks, Azure, AWS, or GCP. Strong Python and data engineering skills. Experience implementing reliable human-in-the-loop AI workflows. Ability to build and deploy production-grade—not just prototype—AI solutions. Preferred Databricks Mosaic AI, Anthropic Claude, Unity Catalog, Vector Search, Agentic RAG, enterprise AI governance, banking or other regulated-industry experience. Recruiter Keywords Agentic AI | AI Agents | Multi-Agent Systems | LangGraph | Generative AI | LLM | RAG | Databricks | Mosaic AI | Python | Anthropic Claude | Vector Search | Human-in-the-Loop | AI/ML Engineering | Data Engineering This is a remote position.