AI Engineer
Posted 3 Mar 2026
Advertised as “Principal AI Engineer – Automation & AI”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 6–10 yrs
- Management level
- People management
- Employment
- Remote
No salary listed for this role.
Field of studyComputer Science, Data Science, Engineering (or related)
Study levelBachelor's
eClinical Solutions is a global leader in clinical data intelligence, delivering the elluminate® Clinical Data Cloud® — an AI-powered platform driving agentic data review, SDTM automation, and RBQM for 18 of the top 50 pharmaceutical companies worldwide.
As part of our eNOVA AI-First transformation, we are embedding AI across every pillar of clinical development and enterprise operations — compressing cycle times, improving data quality, and redefining how work gets done.
As we scale our AI capabilities, we are building a high-impact, hands-on AI engineering function focused on delivering real, production-grade automation across the enterprise.
You will make an impact:
The Principal AI Engineer – Automation & AI is a hands-on technical leader responsible for designing, building, and deploying AI-powered automation solutions across eClinical Solutions.
This role is builder-first (70–80% hands-on development) and operates within a small, high-output team (2–4 engineers). You will work directly with the CTAO and business leaders to identify high-value use cases and rapidly translate them into working AI systems in production.
This is not a program management or oversight role. You are expected to build, ship, and iterate continuously, leveraging modern AI tooling and agentic frameworks to deliver measurable impact.
Accelerate your skills and career within a fast-growing company while impacting the future of healthcare.
Your day to day:
Building & Shipping AI Systems
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Design and deploy agentic AI workflows and automation solutions across enterprise functions including R&D, Engineering, Professional Services, IT, Finance, Sales, and Marketing
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Build production-grade systems such as:
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Multi-agent workflows
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RAG-based applications
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Document intelligence and summarization pipelines
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Workflow and process automation solutions
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Use modern AI tools and frameworks including:
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Codex, Claude Code, Gemini, NotebookLM
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LangChain, LangGraph, LlamaIndex (or equivalents)
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Rapidly prototype, validate, and deploy solutions in weeks, not months
Owning End-to-End Delivery
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Translate business problems into working AI systems
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Design lightweight architectures and iterate quickly