Expert Manager, 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 we 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**

Working alongside our generalist consultants, Bain's Advanced Analytics Group (AAG) helps clients across industries solve their biggest problems using our expertise in data science and engineering. Stationed in our global offices, AAG team members hold advanced degrees in computer science, engineering, AI, data science, physics, statistics, mathematics, and other quantitative disciplines, with backgrounds in a variety of fields including tech, data science, and academia.

**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
- 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
- Defining and implementing scalable, observable, manageable, and self-healing cloud-based solutions across AWS, Google Cloud and Azure
- Collaborate with cross-functional teams, including product managers, data scientists, and other engineers, to define and implement analytics and AI features and functionality that meet business requirements and user needs.
- 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.
- Participate in code reviews and contribute to the establishment and enforcement of coding standards and best practices to ensure high-quality, maintainable code.
- Stay current with emerging trends and technologies in cloud computing, data analytics, and software engineering, and proactively identify opportunities to enhance the capabilities of the analytics platform.
- Collaborate closely with and influence business consulting staff and leaders as part of multi-disciplinary teams to assess opportunities and develop analytics solutions for Bain clients across a variety of sectors.

**ABOUT YOU**
- Master’s degree in Computer Science, Engineering, or a related technical field.
- 10+ years 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
- Exposure to LLMs, Prompt engineering, Langchain a plus
- 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 commu