Application Support Engineer

As an Application Support Engineer on the AI Platform, you'll keep the foundation Aflac runs its agentic AI on healthy across environments: an AWS native, secure, highly scalable platform that other engineering and product teams build on top of. Orchestration, tools, memory, identity, guardrails, evaluation and observability. You'll provide Level 2 and Level 3 support across the platform and the use cases that run on it and help make it production ready from the start rather than after go live.

Agentic systems are non-deterministic, so the support bar is higher than it looks. Anyone can make an agent work once. You'll help keep it working reliably, observably, safely, and at a cost the business can defend. That means treating monitoring, tracing, runbooks and incident response as first class engineering, not afterthoughts. In line with our 'Prevention is better than the Cure' approach, you'll get to the root cause and put measures in place that stop issues coming back.

Serving as a technical owner, you'll use AI as a force multiplier and human amplifier to triage faster, automate routine work, and continually improve the production environment. You'll also be a trusted partner to the teams that use the platform, translating technical issues into plain language, and bringing what you learn in production back into the roadmap.

This is an opportunity to

• Shape how an enterprise supports agentic AI in production
• Build the operational controls, runbooks and monitoring while the decisions are still open
• Work hands on with the newest AWS AI services at production scale
• Solve genuinely hard problems in the reliability, observability and cost of agentic systems
• Grow from application support into AI platform and site reliability engineering
• Build something from the ground up and leave a lasting impact

The AI Services team helps transform how Aflac uses AI at scale where it matters. Taking priority use cases from concept to production, proving what works early, and packaging the results so other teams can repeat them. This team leads Aflac's AI harness engineering methodology, equipping engineers and product teams with AI driven workflows and setting SDLC standards that make AI available, safe and scalable.

The Agentic Platform is the enterprise foundation for that ambition, and we are building it now from first principles. Agent orchestration, tool and MCP server registries, memory and state, identity and access, guardrails, tracing, cost control and self service onboarding.

AI Services Engineering runs as two functions. This role sits in the AI Platform function, owning the Agentic Platform: how Aflac runs agents at scale, cost efficiently and securely, with the right risk posture and robust operational controls. The other function is Context Engineering, taking AI native products from concept to production and setting the AI harness engineering methodology behind them.

Alongside both sits AI Enablement, driving adoption, education and communication across the business. Two sides of one engineering team, working closely with the full AI Services team. You'll work with Platform Engineers to make the platform production ready and keep it that way, and with Context Engineering, Solution Architects, Enterprise Architecture, Security and QA in an agile environment.

Our teams take full product ownership from design through to deployment, with a proactive support model that includes incident management and a rotational on-call function. Core support hours are UK based, from 9am to 5pm, with on-call coverage as required.

• Provide Level 2 and Level 3 support for the Agentic Platform and the AI use cases that run on it, including triage, investigation and resolution
• Operate in a core hour support model from 9am to 5pm UK time, and take part in an on-call rota for out of hours and weekend support
• Lead problem management and blameless post incident reviews, and turn findings into lasting fixes
• Support teams onboarding to the platform, and feed support insight back into the roadmap
• Work with internal teams and third party vendors to troubleshoot and resolve complex problems

• Define and track service level objectives for availability, latency, quality and cost
• Build and maintain monitoring, tracing and alerting across agents, models, tools, MCP servers and AWS infrastructure
• Monitor AI specific signals, including evaluation scores, quality drift, guardrail triggers, tool…