Senior Platform Engineer, Generative AI Infrastructure
$140k - $200kBIP
Job Description
Company Overview:
\n \nBusiness 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.
\n \nWith 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.
\n \nAs 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.
\n \nPosition Overview:
\n \nWe are seeking an experienced Senior Platform Engineer with 7–10+ years of experience to support the design, build, and operational management of infrastructure powering enterprise Generative AI applications. This role will focus on building and maintaining scalable environments that support AI-driven workloads across development, testing, and production.
\n \nThe ideal candidate will have strong experience in platform engineering, DevOps practices, containerized environments, and distributed systems, with the ability to support high-performance computing workloads and modern AI application stacks.
\n \nThis individual will work closely with engineering, data science, and platform teams to ensure reliable, scalable, and efficient infrastructure supporting the development and deployment of advanced AI solutions.
\n \nKey Responsibilities:
\n \nPlatform Architecture & Environment Management
\n- \n
- Design, implement, and maintain scalable platform environments supporting AI and data-driven applications from proof-of-concept through production deployment. \n
- Manage environment dependencies across infrastructure, applications, data services, and networking layers. \n
Infrastructure Automation & DevOps
\n- \n
- Build and maintain automated processes for provisioning, installation, configuration validation, monitoring, and deployment of platform components. \n
- Implement and support CI/CD pipelines to streamline development workflows and accelerate releases. \n
Platform Standardization & Best Practices
\n- \n
- Define and enforce standards for platform configuration, environment management, and infrastructure governance. \n
- Maintain version-controlled inventories of platform environments, configurations, and deployment artifacts. \n
Containerization & Distributed Systems
\n- \n
- Support containerized deployment models using technologies such as Docker and Kubernetes or similar orchestration platforms. \n
- Ensure scalability, reliability, and efficient resource utilization across distributed infrastructure environments. \n
Monitoring, Performance & Optimization
\n- \n
- Implement infrastructure monitoring solutions to track CPU, GPU, memory utilization, inference latency, and system performance. \n
- Identify performance bottlenecks and optimize infrastructure to improve throughput, efficiency, and latency. \n
Deployment & Operational Support
\n- \n
- Collaborate with engineering and operational teams to deploy applications and support production environments. \n
- Troubleshoot and resolve infrastructure, configuration, and environment-related issues. \n
Capacity Planning & Environment Allocation
\n- \n
- Manage environment capacity and allocate resources across teams based on project lifecycle requirements. \n
- Work with project teams to optimize infrastructure costs while maintaining performance and scalability. \n
Required Qualifications:
\n- \n
- 7–10+ years of experience in platform engineering, DevOps engineering, infrastructure engineering, or similar technical roles. \n
- Proven experience designing and maintaining end-to-end platform environments from development through production. \n
- Strong understanding of hardware, software, networking, and application configuration dependencies. \n
- Experience working with CI/CD pipelines and DevOps tooling. \n
- Experience supporting containerized and distributed application architectures using technologies such as Docker and Kubernetes or similar orchestration platforms. \n
- Experience working with microservices, serverless architectures, or loosely coupled distributed systems. \n
- Familiarity with both cloud-based and on-premises infrastructure environments. \n
- Experience working with relational and NoSQL databases, object storage, or large-scale data environments. \n
- Strong scripting skills in Unix/Linux environments, including automation and scheduling tools. \n
- Experience implementing high availability, load balancing, and disaster recovery strategies. \n
Preferred Qualifications:
\n- \n
- Experience supporting AI, machine learning, or Generative AI infrastructure environments. \n
- Familiarity with Python-based application stacks and AI frameworks such as TensorFlow or PyTorch. \n
- Experience managing GPU-based compute environments, including resource scheduling and scaling. \n
- Experience with inference optimization, performance tuning, and infrastructure monitoring for AI workloads. \n
- Prior experience supporting high-performance computing or data-intensive environments. \n
- Experience working in financial services or other highly regulated enterprise environments. \n
**The base salary range for this role is $140,000 - $200,000, with flexibility for exceptional candidates**
\n \nBenefits:
\n- \n
- Choice of medical, dental, vision insurance. \n
- Voluntary benefits. \n
- Short- and long-term disability. \n
- HSA and FSAs. \n
- Matching 401k. \n
- Discretionary performance bonus. \n
- Employee referral bonus. \n
- Employee assistance program. \n
- 11 public holidays. \n
- 20 days PTO. \n
- 7 Sick Days. \n
- PTO buy and sell program. \n
- Volunteer days. \n
- Paid parental leave. \n
- Remote/hybrid work environment support. \n
For more information about BIP US, visit
\n \nEqual Employment Opportunity:
\n \nIt is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.
\n \nBIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.
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