Back End Developer Jobs Opening in Biogen Capability Center India Private limited at Bengaluru

Please Look AWS),  Databricks, Snowflake, and ETL tools with Generative AI initiatives.

Senior Developer - Unstructured Data Processing

Unstructured data processing is a key component for any Generative AI solution, and we are seeking a strong engineer in this area.

 This capability will support enterprise-wide projects and enable us to deliver high-value Generative AI initiatives.

 Responsibilities:

• Understand various document types and extraction methods of information from these documents

• Experience in tools such as Databricks, Snowflake, and ETL tools

• Experience in building Generative AI capabilities

• Experience in building end-to-end pipelines for data sourcing, extraction, vectorization and storing information in multiple target databases

• Develop business processes for operationalization of selected vendor tool

• Build evaluation framework of extraction accuracy, and optimization

• Setup and train developer team on new tool features, and functionality

• 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.

Applicable to both positions:

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.