Staff Engineer, AI/LLM Platform
Summary
Senior applied engineer on a lean AI team building the agentic platform for Simulations Plus's drug-development modeling software: MCP servers exposing scientific engines, context/RAG knowledge layers, and customer-facing agent flows. Day-to-day is Node.js/TypeScript engineering with Anthropic/OpenAI SDKs, vector stores, and evals.
Simulations Plus stands as a global leader in model-informed and AI-accelerated drug development. We create value for our clients by accelerating the discovery, development, and commercialization of pharmaceuticals and other products through innovative science-based software and consulting solutions.
Leadership truly cares about maintaining a positive culture and employee well-being. We offer fully remote work, flexible schedules, and generous vacation policy along with affordable health coverage, annual bonus, and more! Check out how much our employees love working here: .
The Staff Engineer, AI/LLM Platform will be the senior applied engineer on the AI side of a small department whose charter spans both web/SaaS and AI/agents products. The role will help design, build, and distribute the agentic, context, and tool layers that turn decades of scientific modeling and simulation capability into agent-driven product experiences — from MCP servers that expose our core scientific engines, through the context and knowledge systems that feed agents, up to the agent flows customers actually interact with. This is an applied engineering role, not a research one, on a deliberately lean, high-leverage team that's growing quickly and intentionally.
Department: Product and Technology
Internal Grade: 11
Direct Reports: No
Status: Exempt
Location: Remote
Job Responsibilities:
- Agent Systems and Product Surfaces
- Help design, build, and distribute the agentic systems that surface our scientific capability to customers
- Build agent loops, orchestration code, and control structures that balance autonomy, cost, and latency
- Make day-to-day decisions on prompts, tools, structured outputs, and provider tradeoffs across Anthropic, OpenAI, and others
- Context, Knowledge and MCP Layer
- Build and operate MCP servers that expose our core scientific engines and product capabilities to agentic clients
- Design and maintain the context-management layer that feeds agents the right information at the right time
- Stand up vector stores, knowledge bases, and retrieval patterns that power both agent reasoning and customer-facing workflows
- Quality & Team Impact
- Build the evals, traces, and feedback loops needed to debug and improve a non-deterministic system
- Contribute to the architectural patterns and technical standards the team builds on
- Mentor engineers contributing to AI features and raise the floor on applied-AI practice across the team
- Other Duties as Assigned
Required Qualifications:
- 5+ years of professional software engineering experience, with recent production work on agents, LLM-integrated features, or MCP and tool servers
- Strong Node.js and TypeScript background; comfort designing service-layer code and tool integrations
- Working knowledge of agent orchestration, prompt and tool design, and context-management patterns (RAG, vector search, memory)
- Hands-on experience with at least one major LLM provider SDK (Anthropic, OpenAI, or comparable)
- Pragmatic, applied mindset — this is an engineering role, not a research or data-science role
- Fluency using AI coding tools (Claude, Cursor, Copilot) in daily workflow, and comfort working across languages by leveraging them
Preferred Qualifications:
- Python proficiency for prototyping, evals, or interfacing with ML tooling
- Experience with agent frameworks such as LangGraph, Mastra, Pydantic AI, or LlamaIndex — with the judgment to know when not to use them
- Familiarity with vector databases and RAG patterns (Pinecone, pgvector, MongoDB Atlas Vector Search, or comparable)
- Experience in regulated-software environments (SOC 2, HIPAA, GxP, 21 CFR Part 11) or life-sciences SaaS
- Open-source contributions to MCP servers, agent frameworks, or LLM tooling
Education:
- Bachelor's degree in computer science, engineering, or related field preferred
- Master’s degree in computer science, engineering or related field a plus
- Relevant technical certifications welcomed
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