Principal AI Engineer – Automation & AI

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

• Design and deploy agentic AI workflows and automation solutions across enterprise functions including R&D, Engineering, Professional Services, IT, Finance, Sales, and Marketing

• Build production-grade systems such as:

• Multi-agent workflows
• RAG-based applications
• Document intelligence and summarization pipelines

• Workflow and process automation solutions

• Use modern AI tools and frameworks including:

• Codex, Claude Code, Gemini, NotebookLM

• LangChain, LangGraph, LlamaIndex (or equivalents)

• Rapidly prototype, validate, and deploy solutions in weeks, not months

Owning End-to-End Delivery

• Translate business problems into working AI systems
• Design lightweight architectures and iterate quickly

• Develop and implement:

• Prompt engineering strategies
• Orchestration logic
• API integrations and data pipelines

• Testing, validation, and monitoring frameworks

• Partner directly with stakeholders to refine outputs and drive adoption

Driving High-Velocity Execution

• Deliver continuous output with weekly or bi-weekly releases

• Prioritize use cases based on:

• ROI and business impact
• Technical feasibility

• Speed to value

• Operate with minimal process and high accountability in a fast-paced environment

Contributing to Scalable AI Foundations

• Build and maintain reusable assets including:

• Prompt templates
• Agent design patterns

• Integration utilities

• Contribute to lightweight standards for:

• Security and data handling
• Responsible AI practices
• Evaluation and performance monitoring

Technical Leadership & Mentorship

• Provide technical guidance to a small team of AI engineers and automation specialists
• Lead by example through hands-on contribution
• Support the evolution of the AI engineering function as it scales

Take the first step towards your dream career. Here is what we are looking for in this role.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
• 6–10+ years of software engineering experience with recent hands-on work in AI/LLM systems

• Proven experience building and deploying:

• LLM-powered applications
• Agentic workflows

• Automation solutions in production environments

• Strong hands-on experience with tools such as:

• Codex, Claude Code, Gemini, NotebookLM (or similar AI-assisted development tools)

• LangChain, LangGraph, LlamaIndex, or equivalent frameworks

• Proficiency in:

• Python
• API development and system integration
• Cloud platforms (AWS, Azure, or GCP)

Preferred

• Experience with:

• RAG architectures and vector databases
• AI evaluation frameworks, guardrails, and monitoring

• Workflow automation tools and enterprise integrations

• Experience working in regulated environments (e.g., life sciences, healthcare, financial services)
• Familiarity with clinical data, CDISC standards, or clinical development workflows
• Experience in high-gro…