Lead, Platform Engineering

WHAT MAKES US A GREAT PLACE TO WORK We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are a Glassdoor Best Place to Work and have maintained a spot in the top four since its founding in 2009. We believe that diversity, inclusion and collaboration are key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. WHO YOU'LL WORK WITH Vector is Bain's integrated digital and analytics capability, bringing together Enterprise Technology and AI, Insights & Solutions (AIS) to deliver cutting‐edge innovation. AIS, formed through the merger of Bain's Advanced Analytics and Innovation & Design teams, is a diverse group of experts in analytics, engineering, product management, and design. Together, we create human‐centric solutions that leverage the power of data and artificial intelligence to drive competitive advantage for our clients. WHAT YOU'LL DO As a Lead Platform Engineer you will design and build cloud‐based distributed systems that solve complex business challenges for some of the world's largest companies. You will draw on your deep software engineering, cloud engineering, and DevOps expertise to design and build technology stacks and platform components that enable cross‐functional AI Engineering teams to create robust, observable and scalable solutions. As a member of a diverse and globally distributed engineering team, you will participate in the full engineering life cycle which includes designing, developing, optimizing, and deploying solutions and infrastructure at the scale of the world's largest companies. CORE RESPONSIBILITIES Cloud solution and distributed systems architecture for full stack AI software and data solutions Collaborate closely with and influence general consulting teams to develop analytics solutions to client business problems, to prioritize and execute those solutions Defining and implementing scalable, observable, manageable, and self‐healing cloud‐based solutions across AWS, Google Cloud and Azure Implementation, testing and management of Infrastructure as Code (IAC) of cloud‐based solutions that may include CI/CD, data integrations, APIs, web and mobile apps, and AI solutions Participate in code reviews and contribute to the establishment and enforcement of coding standards and best practices to ensure high‐quality, maintainable code Utilize Kubernetes and containerization technologies to deploy, manage, and scale analytics applications in cloud environments, ensuring optimal performance and availability. Develop and maintain APIs and microservices to expose analytics functionality to internal and external consumers, adhering to best practices for API design and documentation Implement robust security measures to protect sensitive data and ensure compliance with data privacy regulations and organizational policies. Continuously monitor and troubleshoot application performance, identifying and resolving issues that impact system reliability, latency, and user experience. Influence, educate and directly support the platform engineering capabilities of our clients Stay current with emerging trends and technologies in cloud computing, data analysis, and software engineering, and proactively identify opportunities to enhance the capabilities of the analytics platform ABOUT YOU Master's degree in Computer Science, Engineering, or a related technical field. 5 years minimum experience and atleast 3+ years at Staff level or equivalent Proven experience as a cloud engineer and software engineer within either/or product engineering or professional services organisations Experience designing and delivering cloud-based distributed solutions. GCP, AWS, or Azure certifications are a benefit Experience building infrastructure as code with tools such as Terraform (preferred), Cloud Formation, Pulumi, AWS CDK, CDKTF, etc Deep familiarity with nuances of software development lifecycle One or more configuration management tools: Ansible, Salt, Puppet, or Chef One or more monitoring and analytics platforms: Grafana, Prometheus, Splunk, SumoLogic, NewRelic, DataDog, CloudWatch, Nagios/Icinga CI/CD deployment pipelines (e.g. Github Actions, Jenkins, Travis CI, Gitlab CI, Circle CI)Experience building backend APIs, services and/or integrations with Python Practitioner experience with Kubernetes through services like GKE, EKS or AKS is a benefit Ability to work closely with internal and client teams and stakeholders Use Git as your main tool for versioning and collaborating Knowledge in SRE practices, tools, RCA and monitoring Knowledge in AI‐accelerated practices, tools and frameworks in Platform Engineering for data analysis, monitoring & alerting, performance fine‐tuning and SRE Experience with workflow orchestration – doesn't matter if it's dbt, Beam, Airflow, Luigy, Metaflow, Kubeflow, or any other Experience implementation of large‐scale structured or unstructured databases, orchestration and container technologies such as Docker or Kubernetes Strong interpersonal and communication skills, including the ability to explain and discuss complex engineering technicalities with colleagues and clients from other disciplines at their level of cognition Curiosity, proactivity and critical thinking Strong computer science fundaments in data structures, algorithms, automated testing, object‐oriented programming, performance complexity, and implications of computer architecture on software performance. Strong knowledge in designing API interfaces Knowledge of data architecture, database schema design and database scalability Agile development methodologies Travel frequency and destinations will vary based on project needs. Hybrid role #J-18808-Ljbffr