Senior Cloud Engineer, Gen AI Platform Engineering

BIP US; New York (NY); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401k matching

PTO buy and sell program

Paid parental leave

Job summary

BIP US is seeking a Senior Platform Engineer based in New York with 7–10+ years of experience in building enterprise cloud platforms for AI applications. The role involves designing and engineering cloud infrastructure to support Generative AI solutions across multiple cloud providers like AWS, Azure, and GCP.

The ideal candidate needs expertise in Kubernetes, Infrastructure-as-Code, and DevOps automation. Additional skills in supporting AI/ML workloads are preferred. The position offers a competitive salary range of $140,000 - $200,000, plus comprehensive benefits.

Qualifications

• 7–10+ years of experience in Platform Engineering, Cloud Engineering, or DevOps.
• Experience supporting AI/ML workloads and model‑serving platforms.
• Strong understanding of containerization technologies including Kubernetes.

Responsibilities

• Design and build scalable cloud infrastructure supporting enterprise Generative AI platforms.
• Define engineering standards and technical approaches that align with enterprise platform architecture.
• Implement monitoring, logging, alerting, and distributed tracing across cloud infrastructure.

Skills

Kubernetes

Infrastructure-as-Code

Cloud-native architectures

DevOps automation

AI/ML workloads

Tools

Terraform

CloudFormation

Docker

Job description

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.

Position Overview

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 DevOps 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.

Key Responsibilities

Platform Architecture & Engineering

• 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.

DevOps, Automation & CI/CD

• 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.

Reliability, Observability & Performance Optimization

• 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.

Technical Leadership & Solution Delivery

• Provide technical leadership for complex infrastructure initiatives from design through production deployment.
• Conduct architecture reviews, code reviews, and engineering design sessions.
• Collaborate with architects, software engineers, security teams, and business stakeholders to define scalable technical solutions.
• Research emerging technologies and evaluate new tooling that enhances platform capabilities.

AI Platform Enablement

• Support deployment of enterprise AI applications, model inference endpoints, API gateways, and intelligent agent frameworks.
• Build infrastructure capable of supporting high‑throughput, low‑latency AI serving workloads.
• Collaborate with AI engineering teams supporting Retrieval‑Augmented Generation (RAG), vector databases, and large‑scale data pipelines.
• Help establish best practices for operating secure, scalable AI infrastructure within enterprise environments.

Required Qualifications

• 7–10+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Site Reliability Engineering (SRE), or Infrastructure Engineering.
• Strong hands‑on experience with AWS, Azure, and/or Google Cloud Platform (multi‑cloud experience strongly preferred).
• Extensive experience designing and operating Kubernetes environments including EKS, AKS, or GKE.
• Proven experience building Infrastructure-as-Code solutions using tools such as Terraform, CloudFormation, or similar technologies.
• Strong experience designing and maintaining CI/CD pipelines supporting enterprise software delivery.
• Experience supporting highly scalable distributed systems and cloud‑native microservices architectures.
• Strong understanding of containerization technologies including Docker and Kubernetes.
• Experience implementing autoscaling, load balancing, high availability, disaster recovery, and fault tolerance.
• Experience with observability platforms including metrics, centralized logging, monitoring, and distributed tracing.
• Strong knowledge of performance tuning, cloud optimization, and infrastructure scalability.
• Excellent troubleshooting, problem‑solving, and cross‑functional collaboration skills.

Preferred Qualifications

• Experience supporting AI, Machine Learning, or Generative AI production environments.
• Experience deploying model inference endpoints, API gateways, or AI serving infrastructure.
• Familiarity with vector databases, Retrieval‑Augmented Generation (RAG), embedding pipelines, or AI orchestration frameworks.
• Experience supporting GPU‑enabled compute environments or computing intensive workloads.
• Experience working within Financial Services or other highly regulated enterprise environments.
• Familiarity with modern AI frameworks, cloud‑native AI services, and enterprise AI platform architectures.
• Experience supporting shared, multi‑tenant enterprise platforms serving multiple engineering teams.

Benefits & Salary

The base salary range for this role is $140,000 - $200,000, with flexibility for exceptional candidates.

• Choice of medical, dental, vision insurance.
• Voluntary benefits.
• Short‑ and long‑term disability.
• HSA and FSAs.
• Matching 401k.
• Discretionary performance bonus.
• Employee referral bonus.
• Employee assistance program.
• 11 public holidays.
• 20 days PTO.
• 7 Sick Days.
• PTO buy and sell program.
• Paid parental leave.
• Remote/hybrid work environment support.

Equal Employment Opportunity

It 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.