Software Engineer, API (Python)

About Nexla

Nexla leads as an AI-powered integration platform that consolidates diverse data sources including Data, Documents, Agents, Applications, and APIs into a unified framework. By offering no-code, low-code, and pro-code options, Nexla significantly boosts productivity for data users and developers. Trusted by top-tier companies like DoorDash, LinkedIn, Johnson & Johnson, and LiveRamp, Nexla is recognized in Gartner's Magic Quadrant for Data Integration Tools and highly rated by users.

Role Overview

As a Software Engineer, you'll be part of a small, dynamic team working on the entire stack of Nexla's SaaS platform, focusing on APIs, data models, background jobs, and integrations using Python and FastAPI. You'll be responsible for designing, developing, deploying, and maintaining platform features without detailed specifications, taking ownership from concept to production.

Key Responsibilities

• Develop end-to-end platform capabilities including data models, APIs, deployment processes, and comprehensive testing.
• Manage internal and customer-facing APIs, ensuring their performance, stability, and ease of integration for other teams.
• Design and maintain database schemas, queries, and migrations for MySQL and Postgres, handling multi-tenancy and background jobs.
• Monitor production code, troubleshoot issues, implement fixes, and create safeguards to prevent recurring problems.
• Split time approximately as 70% coding and shipping, 20% architectural improvements and technical debt reduction, and 10% code reviews, documentation, and mentoring.

Key Challenges

Addressing user requests for environment separation in pipeline building by designing data models and lifecycle management within the existing cloud infrastructure, delivering an exceptional user interface for development, staging, and production environments.

Essential Qualifications

• At least 7 years of professional experience primarily in Python software development with daily use of FastAPI or similar frameworks and SQLAlchemy.
• Strong command over asynchronous programming patterns, dependency injection, and ORM tradeoffs.
• Expertise in SQL and relational database design, query optimization, indexing, and schema normalization.
• Experience with unit and integration testing and pragmatic judgment about test coverage.
• Proven track record of managing production systems with good operational practices like monitoring, alerting, incident handling, and post-mortems.
• Practical experience using AI tools in software development, knowing their strengths and limitations.

Preferred Skills

• Familiarity with cloud platforms such as AWS or GCP including deployment, managed services, and debugging below the application layer.
• Experience with background job managers like Celery or Dramatiq, message brokers such as Kafka or RabbitMQ, and event-driven architectures.
• Background in data-intensive systems or the data integration sector.

Ideal Candidate Attributes

• Demonstrates ownership and proactively commits to projects without waiting for complete specifications or approvals.
• Comfortable defining project scope dynamically and delivering incrementally before the full solution is finalized.
• Focuses on resolving underlying problems rather than just symptoms.
• Creates clear documentation and context for maintainability by others.
• Capable of communicating nuanced technical decisions to non-technical stakeholders.

Work Environment & Process

The role is based in Bengaluru with a hybrid setup requiring two days per week in the office. Coordination with Pacific Time Zone teams for syncs and design reviews is required. The hiring process involves four interviews over approximately two weeks, including coding and API design assessments, with an emphasis on practical AI tool use during coding.

Additional Information

Compensation includes base salary and equity determined by experience rather than title. Nexla is at the forefront of the GenAI data integration revolution, empowering major corporations to transform complex data into actionable assets for AI models.