Lead Full-Stack Engineer (Client Delivery)

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. We are currently the #1 ranked consulting firm on Glassdoor’s Best Places to Work list and have maintained a spot in the top four on Glassdoor’s list since its founding in 2009. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.

WHO YOU’LL WORK WITH

You’ll join our Application Engineering experts within the AI, Insights & Solutions team. This team is part of Bain’s digital capabilities practice, which includes experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you'll leverage deep technical expertise with business acumen to help clients tackle their most transformative challenges. You’ll work on integrated teams alongside our general consultants and clients to develop data-driven strategies and innovative solutions. Together, we create human-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage for our clients. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

WHAT YOU’LL DO

• Design, develop, and maintain cloud-based AI applications, leveraging a full-stack technology stack to deliver high-quality, scalable, and secure solutions. 
• Collaborate with cross-functional teams, including product managers, data scientists, and other engineers, to define and implement analytics features and functionality that meet business requirements and user needs. 
• 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. 
• 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 with DevOps and infrastructure teams to automate deployment and release processes, implement CI/CD pipelines, and optimize the development workflow for the analytics engineering team. 
• 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. 
• Influence, educate and directly support the analytics application engineering capabilities of our clients 
• Travel is required (30%)




• ABOUT YOU

  Required

• Master’s degree in Computer Science, Engineering, or a related technical field.  
• 6+ years at Senior or Staff level, or equivalent 
• Experience with client-side technologies such as React, Angular, Vue.js, HTML and CSS 
• Experience with server-side technologies such as, Django, Flask, Fast API
• Experience with cloud platforms and services (AWS, Azure, GCP) via Terraform Automation (good to have)
• 3+ years of Python expertise
• Use Git as your main tool for versioning and collaborating 
• Experience with DevOps, CI/CD, Github Actions 
• Demonstrated interest with LLMs, Prompt engineering, Langchain
• 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