Lead AI Software Engineer - Hybrid (Bangalore, India)

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Degreed is the upskilling platform that connects learning to opportunities. We integrate everything people use to learn and build their careers—skill insights, LMSs, courses, videos, articles, and projects—and match everyone to growth opportunities that fit their unique skills, roles, and goals.

The Degreed Client Experience (CX) team plays a crucial role in ensuring customer satisfaction and success. The CX teams’ deep knowledge allows them to strategically guide clients, providing tremendous value. The CX team actively participates and assists clients with their learning journeys and transformations. The candidate will be working closely with the CX technical teams to design and maintain client support workflows powered by AI.

This role will be based onsite in Bengaluru, India. After an in-office onboarding period, incumbents are expected to be available in office for a few days per week as part of hybrid work model.  Candidates will also be required to travel internationally 1-2 times annually for full company gatherings.

Day in the Life

• 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 

Who You Are

We seek outstanding individuals to join our outstanding teams. As a Lead AI Software Engineer you not only want to deliver great products, you also want to collaborate with other great engineers:

• 5+ years at Senior or Staff level, or equivalent Software Development Experience
• 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)
• 2+ years of Python 
• Experience with Git for versioning and collaborating 
• Experience with DevOps, CI/CD, Github Actions 
• 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 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