Global It Software Engineer Manager

BCG BCG · Consulting · Gurgaon, Haryana, India · Technology and Engineering

This role involves managing a team responsible for building and operating foundational infrastructure, cloud platforms, software, and DevSecOps capabilities that power enterprise data products and GenAI use cases. The focus is on backend service development, data integration, pipeline management, technical operations, and stakeholder collaboration, with a specific emphasis on designing and implementing GenAI workflows and solutions.

What you'd actually do

  1. Backend service development and delivery
  2. Lead the onboarding and integration of proprietary and third-party datasets into Snowflake and related applications.
  3. Design, develop, document, and maintain robust containerized solutions and/or data pipelines, ensuring seamless ingestion, migration, and rigorous testing.
  4. Actively monitor and troubleshoot production issues across distributed systems and cloud infrastructure, minimizing disruption.
  5. Design and implement MCP-, Skills-, and Agent-based GenAI workflows and solutions.

Skills

Required

  • Python
  • Java
  • Go
  • REST
  • GraphQL
  • event-driven architectures
  • AWS
  • Azure
  • CI/CD pipelines
  • GitOps
  • Docker
  • Kubernetes
  • Agile tools (JIRA, Confluence)
  • Snowflake
  • Glue
  • Airflow
  • AWS S3
  • Azure Blob Store
  • Google Cloud Storage
  • MCP-based GenAI workflows
  • Skills-based GenAI workflows
  • Agent-based GenAI workflows

Nice to have

  • modern API/microservice design
  • modern engineering practices
  • Meta Scrum
  • data strategy

What the JD emphasized

  • enterprise-grade use of GenAI
  • powering enterprise data products and GenAI use cases
  • production services are powering Gen-AI solutions
  • Design and implement MCP-, Skills-, and Agent-based GenAI workflows and solutions
  • 8+ years of experience in Software or Platform Engineering, including Data and AI focused roles/projects
  • Demonstrated proficiency with technologies including Python, APIs, Lambda and batch compute, K8s, as well as orchestration, observability and audit trails for compliance.

Other signals

  • enterprise-grade use of GenAI
  • powering enterprise data products and GenAI use cases
  • production services are powering Gen-AI solutions
  • Design and implement MCP-, Skills-, and Agent-based GenAI workflows and solutions