At BGBx, we're driven by a simple idea: breakthrough thinking creates breakthrough impact. As an independent commercial solutions partner to pharmaceutical and life science companies, we bring together strategists, scientists, communicators, creatives, technologists, and data experts to tackle some of healthcare's most important challenges.
Our teams work across consulting and communications to help clients shape strategy, launch innovations, engage stakeholders, and drive meaningful results throughout the product lifecycle. The work is complex, fast-moving, and deeply connected to improving lives, creating opportunities for curious minds to make a real difference every day.
If you're energized by collaboration, inspired by innovation, and motivated by work that matters, you'll find a place to grow, contribute, and make a meaningful impact at BGBx.
Agentic Platform Architect / Systems Administrator
Position Overview
The Agentic Platform Architect / Systems Administrator owns the technical environment that enables BGB to move from isolated AI experimentation to a secure, governed, and scalable AI operating model. This role designs, implements, secures, and maintains the infrastructure for LLM orchestration, agentic workflows, Cortex-style memory, Claims Library services, knowledge repositories, data pipelines, and automation platforms. The role bridges enterprise systems administration, cloud infrastructure, AI operations, security, and platform engineering so internal AI capabilities can be deployed reliably across the agency.
The Agentic Platform Architect / Systems Administrator builds and operates the secure technical foundation for agents, orchestration, memory, and enterprise AI services.
Primary Mission
Translate the AI vision into a resilient, governed platform architecture that can scale across workstreams and teams.
Key Partners
AI Product Manager, AI Software Engineer, IT/Security, Data/Analytics, Operations, Fourier/implementation partners, functional champions.
Success Measures
Platform uptime, secure access, workflow reliability, integration readiness, auditability, cost visibility, and faster agent deployment.
Responsibilities
- Design, implement, and maintain the infrastructure that supports internal AI platforms, LLM services, agent orchestration, vector databases, RAG pipelines, and automation services.
- Architect the technical foundation for core AI operating model components, including the Orchestration Engine, Claims Library, Cortex/memory layer, GPT portfolio, and agentic workflow environments.
- Administer cloud, hybrid, and enterprise environments that support AI workloads, with clear standards for scalability, resiliency, disaster recovery, access, and cost management.
- Implement authentication, authorization, RBAC, secrets management, identity controls, environment separation, and enterprise security requirements for AI-enabled systems.
- Establish CI/CD pipelines, infrastructure-as-code, deployment workflows, automated provisioning, and release controls for AI agents, services, skills, and integrations.
- Monitor platform reliability, performance, telemetry, token/usage consumption, cost drivers, latency, error rates, and system health across AI environments.
- Support secure integrations between AI systems and enterprise platforms such as Adobe, Figma, Microsoft, project management tools, DAM/content systems, analytics environments, and internal knowledge repositories.
- Operationalize governance controls for model access, prompt and output logging, audit trails, data retention, protected content, human review checkpoints, and environment-level guardrails.
- Partner with engineering and product to evaluate build-versus-buy options, vendor architectures, integration patterns, and long-term platform scalability.
- Troubleshoot infrastructure, deployment, data-flow, access, performance, and operational issues that affect AI workflow delivery.
- Enables the AI operating model to scale beyond pilots by creating the secure technical backbone for agents, GPTs, orchestration, and memory.
- Owns the infrastructure layer that allows reusable intelligence, standardized workflows, and governed automation to become part of everyday operations.
- Protects quality, security, and cost efficiency as AI usage increases across departments and client workstreams.
Qualifications
- 5+ years of systems administration, DevOps, cloud engineering, platform engineering, or infrastructure engineering experience.
- Experience supporting AI/ML, LLM, automation, workflow orchestration, or enterprise software environments.
- Strong knowledge of AWS, Azure, or GCP, including identity, networking, storage, monitoring, security, and cost management.
- Experience with Docker, Kubernetes, CI/CD, infrastructure-as-code, scripting, observability tooling, and automated deployment practices.
- Working knowledge of LLM operations, vector databases, embeddings, RAG architectures, API-based integrations, and secure data exchange patterns.
- Understanding of enterprise security, privacy, compliance, audit logging, and governance requirements for internal and client-adjacent AI systems.
- Ability to translate business and product requirements into practical technical architecture and operating standards.
- Demonstrated experience using AI tools as an active part of your development or product workflow.
Salary Range: £65,000 - £75,000 GBP
BGBx is an equal opportunity employer. All applicants will be considered without regard to race, color, religion, sex, age, national origin, citizenship status, sexual orientation, disability, veteran status or any category or class of person protected by law.
