This role is for one of our clients
As the Senior Director of Engineering lays out the architectural vision and scales the team, this role is the execution anchor. You will be the person who turns that vision into shipped, production-grade software — owning critical platform components end-to-end and being the engineer others look to when things get hard.
What You Will Do
Platform Engineering
- Own and evolve core platform services: document ingestion pipelines, search and retrieval infrastructure, API layer, and data models.
- Deliver features from design to production with a high bar for reliability, performance, and maintainability.
- Participate meaningfully in architecture reviews and proactively propose improvements to the codebase and system design.
- Write clean, well-tested, well-documented code and hold the team to the same standard through rigorous code review.
AI & Intelligence Features
- Build and maintain the AI-powered features at the heart of the platform: RAG pipelines, LLM-based document analysis, entity extraction, regulatory signal detection, and summarisation.
- Evaluate and integrate new AI models, embedding techniques, and orchestration frameworks as the landscape evolves.
- Debug and improve AI pipeline quality — including retrieval relevance, hallucination detection, and output accuracy in high-stakes regulatory contexts.
- Collaborate with the Senior Director / Head of Engineering to prototype and validate new AI-driven capabilities before committing to full build-out.
Technical Leadership (Emerging)
- Act as deputy to the Senior Director / Head of Engineering — step up during their absence and keep engineering momentum moving.
- Mentor and technically guide junior or mid-level engineers on the team.
- Help define and uphold engineering standards: PR review culture, testing practices, deployment processes, and documentation norms.
- Contribute to hiring by participating in technical interviews and calibrating candidate assessments.
Cross-functional Collaboration
- Work closely with the regulatory operations team to understand domain workflows and translate them into precise technical requirements.
- Engage directly with product and design to refine features, challenge assumptions, and surface technical constraints early.
- Occasionally join customer calls or demos to provide technical depth and capture feedback first-hand.
What We Are Looking For
Core Technical Skills
- 7–11 years of software engineering experience, with at least 3–5 years working on production SaaS platforms.
- Strong proficiency in Python for backend services, data pipelines, and AI/ML integrations.
- Hands-on experience building and deploying LLM-powered features: prompt engineering, RAG architectures, vector databases (e.g., Pinecone, Weaviate, pgvector), and LLM APIs (OpenAI, Anthropic, or open-source equivalents).
- Solid understanding of cloud-native infrastructure (AWS preferred), containerisation (Docker/Kubernetes), and CI/CD practices.
- Experience with REST and/or GraphQL API design and a track record of building APIs that other teams depend on.
- Comfortable with modern frontend frameworks (React) — not required to be a specialist, but should be able to contribute across the stack when needed.
Domain Knowledge
- Strongly Preferred: Understanding of the regulatory landscape in life sciences or healthcare — familiarity with FDA, EMA, ICH, or equivalent agencies, document types (guidance, eCTD, dossiers), and compliance workflows.
- Acceptable Alternative: Experience building software for a regulated life sciences environment — clinical trial platforms, pharmacovigilance, healthcare informatics, or medical device compliance.
- Valued Mindset: Ability to read and reason about regulatory documents, understand their structure, and think about what intelligent extraction and retrieval would look like.
Soft Skills & Mindset
- High ownership — you treat the platform as yours and feel personally invested in its quality.
- Strong written and verbal communication — you can explain technical decisions clearly to non-engineers.
- Comfortable with ambiguity — you can operate well even when requirements are still being defined.
- Collaborative but opinionated — you push back constructively, seek alignment, and then execute decisively.
- Growth orientation — actively looking to develop leadership skills and take on more responsibility over time.
Technical Environment
- AI/ML: LLM APIs, vector databases, embedding pipelines, document parsing and OCR tooling, orchestration frameworks (LangChain, LlamaIndex, or equivalent)
- Backend: Python services, REST / GraphQL APIs, async processing, event-driven pipelines
- Cloud: AWS, Docker/Kubernetes, Terraform or equivalent IaC, GitHub Actions CI/CD
- Data: Structured and unstructured document stores, search indexes, relational databases
- Frontend: React ecosystem — contribution welcome but not the primary focus of this role
Growth Path
This role is explicitly designed with a progression arc in mind, with increased scope over architecture decisions, team mentorship, and stakeholder representation. High performers are given the runway to grow as fast as the organisation does.
Why This Role
Real OwnershipYou will own meaningful parts of a production platform — not just tickets in a queue.
AI at the CoreLLMs and intelligent retrieval are the product, not an add-on. You will build the intelligence layer.
Clear Growth PathAn explicit path is built into this role from day one.
Impactful DomainRegulatory compliance directly affects patient safety. The work has real-world consequences worth caring about.
Small Team, Big ScopeYour contributions are highly visible and directly shape company outcomes.
