Note: The job is a remote job and is open to candidates in USA. Vertex Inc. is a company focused on AI solutions, and they are seeking a Principal AI Engineer to define the orchestration and retrieval systems of their central AI system. This role involves designing and building systems that connect large language models to various tools and data while mentoring engineers and enhancing team maturity.
Responsibilities
- Design the orchestration and abstraction layers of the central AI system that connect LLMs to tools, data, and sub-agents
- Design, build, and operate MCP (Model Context Protocol) servers and set standards for how tools are defined, exposed, and versioned
- Define tool-surface strategy: the optimal number of tools exposed to an LLM, the optimal number of APIs per MCP server, and how to keep tool surfaces coherent and discoverable
- Establish when to use specialized sub-agents versus directly exposing tools to a model, and design the corresponding multi-agent patterns
- Design retrieval (RAG) systems: chunking strategies, embedding models, vector stores, hybrid/keyword search, re-ranking, and context assembly
- Define abstraction layers that decouple product teams from the underlying models, tools, and providers
- Build routing, context-window management, and memory strategies for agentic workflows
- Define evaluation for orchestration and retrieval quality (retrieval precision/recall, tool-selection accuracy, task success, latency, and cost)
- Establish observability and tracing across multi-step agent and tool calls
- Address safety, guardrails, authentication, and access control across tools and agents
- Partner with product teams to onboard their capabilities as tools and agents into the central AI system
- Mentor engineers and raise orchestration and retrieval maturity across teams
Skills
- Bachelor's degree in Computer Science, Engineering, or related discipline
- 12 or more years of experience in software/AI engineering, with hands-on experience building LLM orchestration, agents, and retrieval systems
- Deep hands-on experience with LLM orchestration frameworks (e.g., LangGraph, LlamaIndex, Semantic Kernel, or equivalents) and agentic patterns
- Direct experience building MCP servers and tool/function-calling integrations
- Evidence-based opinions on the optimal number of tools to expose to an LLM and the optimal number of APIs per MCP server, and on overall tool-surface design
- A clear, defensible point of view on specialized sub-agents versus direct tool exposure, and the tradeoffs of each
- Deep experience with retrieval/RAG: chunking strategies, embeddings, vector databases, hybrid search, and re-ranking
- Experience designing abstraction layers and platform APIs that many teams build on top of
- Strong understanding of context-window management, prompt/context assembly, and cost/latency optimization
- Experience with evaluation and observability for agentic and retrieval systems
- Ability to set strategy and standards while remaining hands-on in code
- Strong stakeholder collaboration and problem-solving skills
- Advanced degree preferred
Benefits
- Vertex Bonus Plan (VOB)
- Role-specific sales commission/bonus
- Equity grants
- Base pay offered to new hires may vary based upon factors including relevant industry and job-related skills and experience, geographic location, and business needs.
Company Overview
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