Production Support Engineer (L2, Customer-Facing)

Sits within a newly acquired startup building an AI-enabled, autonomous banking platform for Tier-1 financial institutions within the banking group. The Production Support Engineer diagnoses, troubleshoots, and resolves complex production and customer issues across modern banking platform environments. This is a level 2 role: the engineer takes tickets directly from Tier-1 banks, with no first-line team in front, reproduces issues and hands them to the owning engineering team with clear evidence, and keeps the customer informed throughout. The role is hands-on and customer-facing, requiring strong investigation skills, clear communication, and the ability to connect application behavior, Kubernetes infrastructure, logs, metrics, and customer impact. The role offers an advancement path into platform engineering for those who want to grow in that direction.

KEY RESPONSIBILITIES

Technical Troubleshooting & Incident Resolution

• Investigate and resolve complex technical issues across application, infrastructure, and platform layers.
• Analyze logs, metrics, traces, and alerts to identify root causes and correlate symptoms across systems.
• Troubleshoot Kubernetes and container issues, including pods, services, deployments, networking, and resources.
• Reproduce issues and hand them over to the owning engineering team with logs, traces, timestamps, and steps to reproduce.

Customer-Facing Support

• Engage directly with enterprise banking customers to understand, investigate, and resolve technical issues, including issues caused by changes on the customer's side, such as firewall or network changes, without assigning blame.

• Acknowledge new issues quickly and give customers regular updates while an investigation is open, even when there is no news.

• Communicate findings clearly to technical and non-technical customer stakeholders.

Observability & AI-Assisted Operations

• Use tools such as Prometheus, Grafana, Loki, OpenTelemetry, Datadog, Splunk, or similar to investigate behavior.

• Work with the platform's AI-driven SRE capabilities — incident insights, auto-remediation, and AI-based root cause analysis — validating findings and acting on them.

• Improve runbooks, dashboards, alerts, and support processes based on recurring issues and lessons learned.

Platform Support

• Support Kubernetes-based banking platform environments across multi-cloud (AWS, GCP, Azure), hybrid, and customer-hosted deployments.

• Assist with deployment-related troubleshooting when required; deployment ownership is a plus, not a core requirement.

• In quieter periods, contribute to projects alongside the platform engineering team.

REQUIRED EXPERIENCE & CAPABILITIES

Technical Expertise

• 7 to 12 years of Strong hands-on troubleshooting experience across production or customer-facing technical environments — the single most important capability for this role.

• Working knowledge of Kubernetes: what pods and services are, how traffic reaches the cluster and moves between pods, and how storage works; hands-on troubleshooting with kubectl. Building or running clusters is not required.

• Solid Linux troubleshooting, including processes, memory, disk space, and inodes. The platform does not run on Windows.

• Strong understanding of networking fundamentals, APIs, services, and distributed system behavior. Networking is one of the most common causes of issues on the platform.

• Basic understanding of PostgreSQL or another relational database, such as replication, primary/replica, and active-passive setups. Deep database administration is not required.

• Ability to read, interpret, and correlate logs, metrics, traces, and alerts; comfortable using Grafana dashboards, running metric queries, and following traces. The engineer uses these tools and does not need to have built them.

Customer-Facing Experience (Mandatory)

• At least one proven customer-facing technical role is required.
• Experience working directly with customers during investigations, escalations, or production support scenarios.

Operating Style

• Strong ownership mindset and bias toward resolution.
• Practical, hands-on problem solver who enjoys investigation and troubleshooting.
• Works as a peer within a small team.
• AI-native: integrates LLMs and AI tooling into daily investigation and support work.

PREFERRED EXPERIENCE

• Experience supporting enterprise SaaS, banking platforms, fintech systems, or regulated infrastructure.
• Familiarity with cloud or hybrid environments such as AWS, GCP, Azure, or on-prem enterprise deployments.
• Exposure to deployment workflows, Helm, Terraform, Flux, ArgoCD, Kafka, or distributed databases.
• Awareness of Kubernetes networking plugins (CNI), for example Cilium.

IDEAL CANDIDATE PROFILE

The ideal candidate is someone who enjoys solving difficult problems, working directly with customers, and bringing structure and clarity to complex technical situations. They are hands-on, calm under pressure, and comfortable moving between logs, metrics, customer context, and engineering discussions to get to root cause. This is not an SRE, DevOps, architecture, or platform engineering role, and the engineer does not build or own the infrastructure — engineers looking to architect and build systems will find a better fit in our Platform Engineer openings. For those who want to grow into platform engineering, this role offers a path there, typically over one to two years.

IMPACT & SCOPE

• Direct impact on customer trust, production reliability, and operational continuity for Tier-1 banking institutions.
• High visibility across customer, support, engineering, platform, and product teams.

WHY JOIN

• This role offers the opportunity to support a next-generation banking platform used by some of the world's largest financial institutions. It combines the technical complexity of Kubernetes-based infrastructure, the urgency of production support, and the customer impact of enterprise banking.
• Work alongside the platform engineering team on projects, not only on tickets.
• Gain hands-on exposure to multi-cloud Kubernetes and an AI-driven SRE agent that diagnoses and remediates incidents.
• A clear path into platform engineering for those who want to grow in that direction.

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Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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