Senior Cloud Engineer, Gen AI Platform Engineering

Senior Cloud Engineer, Gen AI Platform Engineering Company Overview:

Business Integration Partners (BIP) is Europe’s fastest growing digital consulting company and is on track to reach the Top 20 globally by 2030. With a growing presence across the United States—including New York, Charlotte, Chicago, and Houston—BIP operates at the intersection of business strategy, technology, and data to deliver impactful solutions for clients.

With more than 6,000 professionals worldwide, BIP partners with organizations across Financial Services, Insurance, Payments, and other industries. Our capabilities span Data & AI, Cybersecurity, Risk & Compliance, Digital Transformation, and Change Management. We combine deep industry expertise with engineering excellence to help clients modernize platforms, unlock data insights, and drive innovation.

As part of our continued expansion in the United States, BIP is strengthening its Capital Markets technology practice. Our teams work closely with trading, risk, and front-office technology organizations to modernize critical platforms, enhance analytics capabilities, and support complex financial product ecosystems.

We are seeking a Senior Platform Engineer with 7–10+ years of experience building and operating enterprise cloud platforms supporting modern AI applications and distributed systems. This individual will play a critical role in designing and engineering the cloud infrastructure that enables secure, scalable deployment of Generative AI solutions across multiple cloud providers.

The ideal candidate possesses deep expertise in platform engineering, Kubernetes, Infrastructure-as-Code, cloud-native architectures, and Dev Ops automation. Experience supporting AI/ML workloads, model-serving platforms, or high-performance distributed systems within regulated enterprise environments is highly preferred.

This role offers the opportunity to build enterprise-scale Generative AI infrastructure while collaborating closely with software engineering, data science, platform engineering, and architecture teams to deliver resilient, production-ready AI capabilities.

• Design and build scalable cloud infrastructure supporting enterprise Generative AI platforms across AWS, Azure, and GCP.
• Define engineering standards and technical approaches that align with enterprise platform architecture.
• Develop secure, highly available infrastructure capable of supporting large-scale AI applications and services.
• Evaluate emerging cloud technologies, platform capabilities, and engineering best practices to continuously improve platform performance.

• Design, implement, and manage Kubernetes environments including EKS, AKS, and GKE.
• Build and maintain cloud-native infrastructure supporting APIs, agent-based applications, and AI model-serving workloads.
• Engineer scalable distributed systems utilizing containerized microservices architectures.
• Implement autoscaling, load balancing, fault tolerance, and disaster recovery strategies.

• Design and maintain enterprise CI/CD pipelines supporting infrastructure and application deployments.
• Automate infrastructure provisioning using Infrastructure-as-Code tools and configuration management frameworks.
• Improve engineering productivity through automation, standardized deployment processes, and release management best practices.
• Continuously optimize deployment pipelines to improve delivery speed, reliability, and security.

• Implement monitoring, logging, alerting, and distributed tracing across cloud infrastructure.
• Optimize platform performance through infrastructure tuning, scaling strategies, and workload optimization.
• Build highly available, resilient environments supporting mission-critical production workloads.
• Partner with engineering teams to troubleshoot complex production issues and improve operational reliability.

• Provide technical leadership for complex infrastructure initiatives from design through production deployment.
• Conduct…