Application Engineer Jobs Opening in Biogen Capability Center India Private limited at Bengaluru
FEATURED JOBSenior Application Developer
organization.
Job Description
Senior Application Developer âÃÂàSolution/Scale Capabilities
Responsibilities:
Containers:
Setup infrastructure to containerize and deploy Applications and supporting databases
Setup scalability for the platform components where appropriate (EKS/ECS) and on-prem containers
Setup monitoring for containers to govern and manage scalability groups
Develop process to optimize infrastructure based on monitoring metrics
Develop/Document best practices for containerization to support scalability and optimize costs.
CI/CD Pipelines:
Setup CI/CD pipelines for code promotion between environments
Test end-to-end CI/CD pipelines once setup is done
Document the processes, train, transition knowledge to developer teams
Constantly review, evaluate and deploy new and emerging capabilities (ex. Agentic AI patterns, prompt templates, vector databases, application patterns, evaluation and optimization frameworks such as LLM as a Judge etc.)
Have continuous improvement mindset to constantly learn, improve and advance AI capabilities.
General Responsibilities:
Infrastructure: Design, deploy, and manage AWS infrastructure to support data science and machine learning pipelines.
Data & Platforms: Set up and optimize infrastructure for vector databases (e.g., Pinecone, Weaviate etc.), unstructured data processing (documents, audio, video), and large-scale data warehousing (Snowflake).
ML/LLM Operations: Implement CI/CD pipelines and automation for model training, serving, and deployment.
Containerization: Architect and manage containerized environments for AI applications using Amazon EKS and ECS, ensuring high availability and scalability.
Tooling: Support data science teams by integrating and managing platforms such as Databricks, Jupyter, and VS Code.
Monitoring & Optimization: Proactively monitor and scale AI/ML infrastructure to ensure optimal performance, resource utilization, and cost efficiency.
Required Skills:
AWS: Expert-level proficiency in core AWS services for AI/ML and data (S3, EC2, EKS, ECS, SageMaker, Lambda, etc.).
Data Platforms: Strong experience with Snowflake and Databricks.
ML/LLM Operations: Hands-on experience with vector databases and processing unstructured data and GenAI/ML Observability.
DevOps: Expertise in DevOps principles, including automation, IaC (e.g., Terraform), and CI/CD pipelines.
Tools: Familiarity with Jupyter notebooks and VS Code environments.
Experience:
7-8 years of architecting hybrid cloud (preferably AWS) solutions using industry leading and cloud native capabilities and tools.
1-2 years of delivering Generative AI solutions.
Works well in a matrix organization with onshore and offshore teams.
Good written and verbal communication skills.
Strong interpersonal skills and continuous learning mindset.
