Staff Solution Support Engineer

Overview

Staff-level leader for GSK's Enterprise AI solutions engineering function, setting architectural standards, governing AI product lifecycles, delivering intelligent operations, and owning production operations for the Enterprise AI portfolio.

What you'll do

• Lead the Solutions Engineering function: strategy, team structure, hiring, development, and standards.
• Hire, mentor, and develop Senior Solutions Engineers, building clear development paths with active coaching and regular feedback.
• Set the architectural and AI engineering standards and integration patterns the whole function operates to, ensuring consistency and quality across all engagements.
• Build and maintain a culture of rigorous documentation, code quality, and knowledge sharing within the SE function.
• Lead the most novel and precedent-setting integrations, staying close enough to the code to make authoritative engineering decisions.
• Establish Product Lifecycle Management (PLM) for Enterprise AI, governing every AI product and model from ideation through scale, operation, and retirement.
• Deliver Intelligent Operations for the Enterprise AI organization using monitoring, automation, and AI-driven tooling.
• Own production operations for Enterprise AI, including KTLO, SLA and service-metric commitments, and strategic supplier delivery.
• Direct a fleet of AI agents and Senior Engineers to continuously improve the cost at which value is delivered, and recognise when solutions must be refactored or optimised as deployments scale.
• Represent EAI's integration architecture with senior GSK technology and enterprise architecture leadership.

What you'll need

• 16+ years in enterprise solution architecture, technical engineering, or equivalent, with significant time leading solutions engineering or architecture functions.
• Recent, hands-on AI engineering experience: personally built and deployed production AI/ML or LLM-based systems (for example RAG, agentic workflows, model serving, evaluation pipelines), and can write, review, and debug code in languages such as Python.
• Experience directing teams of engineers and AI agents (agentic engineering and operations workflows) to deliver at lower cost, with the ability to measure and improve cost against delivered value.
• Deep expertise in enterprise integration patterns (APIs, event-driven architectures, data exchange standards), with a track record of standardising at portfolio scale.
• Practical experience with MLOps/LLMOps and cloud-native deployment (CI/CD, containers, infrastructure as code, observability) sufficient to make authoritative decisions about deployment, integration, and operability at scale.
• Experience designing or operating Product Lifecycle Management (PLM) or equivalent lifecycle governance for technology, data, or AI products, including stage gates, versioning, change control, and retirement.
• Demonstrated ability to deliver intelligent operations: building monitoring, automation, and AIOps capabilities that improve reliability, reduce operational toil, and control cost for production platforms or AI services.
• Experience owning production operations and support for enterprise platforms or AI services, including KTLO, SLA/SLO and service-metric accountability, incident and problem management, and on-call and escalation models.
• Track record of recognising when systems must be refactored or optimised as they scale, and leading that work (performance tuning, re-architecture, cost optimisation) in production.
• Experience managing strategic suppliers or vendors on delivery, including performance reviews, SLA enforcement, escalation, and roadmap alignment.
• Proven ability to build and develop technical teams: hiring, mentoring, setting standards, and creating clear development paths.
• Confidence engaging at senior executive level, representing complex integration strategy to GSK technology leadership, enterprise architecture, and senior business stakeholders.
• Experience operating in a regulated enterprise environment (pharma, healthcare, or financial services preferred).

Nice to have

• Experience leading a Solutions Engineering or technical architecture function at a company with a complex enterprise integration landscape.
• Demonstrated track record of building canonical integration patterns adopted at organisational scale.
• Prior experience in an AI-native company (Anthropic, Palantir, OpenAI, or similar) or equivalent AI-first engineering environment.
• Experience setting AI engineering standards, responsible AI practices, and architectural governance at an organisational level.
• Familiarity with ITIL or SRE practices (error budgets, blameless post-incident reviews, change management) applied to AI and data platforms.
• Familiarity with GxP, computer system validation, or other quality and regulatory frameworks as they apply to AI and software products.
• Experience with agent frameworks, vector and graph data stores, model evaluation and red-teaming, and AI cost management (FinOps).

Details

• Location: Bengaluru Luxor North Tower.