Senior AI Solutions Engineer

Based within Product Development Data Sciences (PDD) , you will serve as the technical lead and architect driving the organization's enterprise AI roadmap. You will transition operational teams from manual data handling to intelligent, automated steering through production-grade AI agents, agentified dashboards, and automated data pipelines.

Key Responsibilities

Here is an overview of the core responsibilities:

• AI Solution Architecture: Design reusable, scalable enterprise AI architectures, multi-agent frameworks, and RAG pipelines across operational workflows.
• Agentic AI & LLMs: Build and deploy agents using modern foundation models (Claude, OpenAI) featuring tool calling, structured outputs, and autonomous multi-agent coordination.
• Agentified Dashboards: Develop interactive, natural-language interfaces and dashboards (R Shiny or Python) over portfolio, resourcing, and operational metrics.
• Shared Foundations: Build and govern a centralized library of reusable AI skills, connectors, and evaluation benchmarks across the organization.
• GxP & Trust by Design: Partner with Quality & Compliance to establish validation pathways, deterministic guardrails, human-in-the-loop controls, and audit trails.
• Technical Leadership & MLOps: Establish CI/CD, testing, containerization, and observability standards; mentor engineers and guide cross-functional teams on AI adoption.

Must-Haves

Candidates must meet the following minimum criteria:

• Experience: 4+ years in software, data, or ML engineering, including 2+ years building production LLM apps, RAG, or autonomous agents.
• Python: Expert-level production Python (FastAPI, Pydantic, asyncio, pytest, packaging).
• Agentic Frameworks: Hands-on experience with frameworks such as LangGraph, AutoGen, CrewAI, or native agent SDKs.
• Data & Cloud: Advanced SQL, cloud data warehouse proficiency (Snowflake preferred), Docker, Git, CI/CD, and AWS deployment.
• Visualization: Solid experience with R Shiny or Shiny for Python.
• Governance & Mindset: Working knowledge of validation, auditability, data privacy, and security (GxP/regulated environment awareness) with strong cross-functional communication skills.

Preferred Qualifications

The following qualifications are advantageous:

• Advanced degree (Master's or Ph.D.) in Computer Science, AI, or a quantitative discipline.
• Experience with in-database AI (e.g., Snowflake Cortex) and agent security/jailbreak defense.
• Background in Pharmaceutical R&D, clinical development, or another heavily regulated sector.
• Classical ML experience (scikit-learn, time-series forecasting) and a strong GitHub/project portfolio.

Randstad Technologies is acting as an Employment Business in relation to this vacancy.