SDE 1 / 2 / 3 (Backend)

As a Backend Developer, you will build the integration and data infrastructure that powers BAIL's enterprise AI products, connecting existing enterprise systems, APIs, and data sources with modern applications and intelligent workflows.

We are looking for Backend Developers (2-8 years) with strong software engineering fundamentals and hands-on experience in backend system integration, API development and integration, and data pipelines. You will work closely with frontend developers, AI engineers, and enterprise technology teams to build reliable backend services that connect existing business systems with BAIL's AI-powered applications. We are technology-stack agnostic. Whether your experience is in Python, Java, Node.js, . NET, Go, or another backend ecosystem, we value strong engineering fundamentals, practical problem-solving, and the ability to work across different technologies.

The core responsibilities for the job include the following:

Build and Integrate Enterprise Backend Systems:

• Design, develop, and maintain scalable backend services that power enterprise AI applications.
• Integrate with existing enterprise systems, internal platforms, databases, and third-party services.
• Build middleware and integration layers to enable seamless communication between legacy systems and modern applications.
• Work with heterogeneous technology environments and adapt to existing enterprise architectures.

Develop and Integrate APIs:

• Build and maintain RESTful APIs and backend services for frontend applications and AI-powered workflows.
• Integrate existing internal and external APIs, handling authentication, data transformations, error handling, and reliability.
• Design reusable service components and API integration patterns.
• Implement secure API communication using appropriate authentication and authorization mechanisms.

Build Data Pipelines and Integration Workflows:

• Develop and maintain data ingestion, transformation, and processing pipelines across multiple data sources.
• Integrate structured and semi-structured data from enterprise databases, APIs, and external platforms.
• Build reliable batch and near-real-time data processing workflows based on business requirements.
• Ensure data quality, consistency, validation, and efficient movement of data across systems.

Engineer for Performance, Reliability, and Scale:

• Develop maintainable, modular, and production-ready backend systems.
• Optimize database queries, API response times, and data processing performance.
• Implement appropriate logging, monitoring, error handling, and troubleshooting mechanisms.
• Write unit and integration tests and participate in code reviews to maintain engineering quality.

Collaborate Across the Stack:

• Partner with frontend developers to define API contracts and deliver seamless application experiences.
• Work with AI/ML engineers to connect AI services, models, and intelligent workflows with enterprise systems.
• Collaborate with product managers, solution architects, and enterprise IT teams to translate business requirements into technical solutions.
• Support deployment, debugging, and continuous improvement of production applications.

Prototypes to Production:

• Build rapid prototypes and proofs-of-concept for enterprise AI use cases.
• Convert successful prototypes into reliable, scalable production services.
• Contribute reusable integration components and backend architecture patterns across BAIL's products.

Requirements:

• Someone who has built and maintained production backend applications and understands how to connect multiple systems into a reliable, cohesive architecture.
• 2-8 years of hands-on backend development experience, preferably with production-grade applications.
• Strong proficiency in at least one backend programming language such as Python, Java, Node.js, C#/. NET, Go, or equivalent.
• Hands-on experience developing, consuming, and integrating RESTful APIs.
• Experience integrating existing enterprise systems, third-party services, and databases.
• Practical experience building data ingestion, transformation, or processing pipelines.
• Strong understanding of SQL, relational databases, and data modeling fundamentals.
• Good knowledge of backend architecture, asynchronous processing, error handling, and system reliability.
• Strong debugging, troubleshooting, and analytical problem-solving skills.
• Experience working with Git, testing frameworks, and modern software development practices.
• Ability to work independently and collaborate across engineering and business teams.
• Comfortable learning new technologies and working with different technology stacks.

Preferred / Good-to-Have Skills:

• Experience with cloud platforms, particularly Microsoft Azure, AWS, or GCP.
• Exposure to Azure Data Factory (ADF), Azure Databricks, or similar cloud-based data integration and processing technologies.
• Experience with ETL/ELT pipelines, orchestration, and data engineering workflows.
• Familiarity with Docker, Kubernetes, CI/CD, and cloud deployments.
• Understanding of event-driven architectures, messaging systems, or streaming technologies.
• Exposure to AI/ML services, LLM APIs, or enterprise AI applications.

Technical Depth we expect:

• Backend Development: Strong programming fundamentals and hands-on experience building production backend services in any modern backend stack.
• System Integration: Ability to connect existing enterprise applications, internal services, third-party platforms, and databases.
• API Development and Integration: Experience building and consuming REST APIs, authentication, request/response handling, error management, and API contracts.
• Data Pipelines: Experience with data ingestion, transformations, batch processing, and data movement between systems.
• Databases: Strong SQL fundamentals, relational database integration, query optimization, and familiarity with NoSQL where relevant.
• Architecture and Reliability: Understanding of modular services, asynchronous processing, scalability, logging, and fault tolerance.
• Testing and Engineering Quality: Unit/integration testing, debugging, Git workflows, maintainable code, and code reviews.
• Cloud and Data Platforms (Bonus): Exposure to Azure, Azure Data Factory, Databricks, AWS, GCP, or similar cloud and data technologies.
• AI Integration (Bonus): Familiarity with integrating AI services, LLM APIs, or AI-driven workflows into backend applications.