Lead Full-Stack AI Engineer (Client Facing Role)

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 currently ranked #1 on Glassdoor's Best Places to Work list, and we have maintained a spot in the top four on Glassdoor's list for the last 13 years. We believe that diversity, inclusion and collaboration is 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.  We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents.

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, customer insights, statistics, machine learning, data management, supply chain analytics and data 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, marketing analytics and academia. We are committed to building a diverse and inclusive team and encourage candidates of all backgrounds to apply

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.  
• 3+ 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)
• 4+ years of Python expertise
• Use Git as your main tool for versioning and collaborating 
• Experience with DevOps, CI/CD, Github Actions 
• Experience 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