Software Engineer, API(Python) New Bengaluru, Karnataka, India

Nexla, Inc.; Bengaluru; Hybrid; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Equity

Hybrid work in Bengaluru

Overlap with Pacific hours

Job summary

Nexla in Bengaluru is hiring a senior software engineer who writes production Python daily using FastAPI. You will work across the full stack of our SaaS platform, shaping APIs, data models, and integrations in a small, high-visibility team.

You’ll own end-to-end features, drive reliability, testing, and production monitoring, and collaborate with US-based leadership. This role is hybrid (2 days in office) with base salary plus equity.

Qualifications

• 7+ years of professional software engineering, with Python as your primary language.
• FastAPI, or a similar async Python framework such as Starlette, plus SQLAlchemy.
• Strong SQL and relational database skills. Normalize schemas, write efficient queries.
• You write unit and integration tests, and you have opinions about what is worth testing.
• Owned production systems with monitoring, alerting, incident response, post-mortems.
• You use AI tools in your work and can say where they help or mislead.

Responsibilities

• Own end-to-end platform features: data model, API, deployment, tests.
• Maintain APIs, internal services, and customer-facing endpoints with performance and reliability in mind.
• Manage the data layer: schemas, migrations across MySQL and Postgres; multi-tenancy considerations.
• Observe production behavior, identify debt, performance bottlenecks, and security gaps; document changes.

Skills

Python

FastAPI

SQL

Async programming

Unit testing

Production systems

AI tooling usage

AWS / GCP

Background job processing

Data-intensive systems

Tools

SQLAlchemy

Celery

Kafka

Redis

PostgreSQL

MySQL

Docker

Job description

Nexla is the leading Integration platform, built with AI, for AI. Nexla takes a metadata driven approach to converge diverse integrations across Data, Documents, Agents, Applications, and APIs into a single design pattern. We accelerate the development of solutions for GenAI, Analytics, and Inter-company data. Nexla makes data users and developers up to 10x more productive by delivering a true blend of no-code, low-code, and pro-code interfaces.

Leading companies including DoorDash, LinkedIn, Johnson & Johnson, and LiveRamp trust Nexla for mission-critical data. Named in the 2022, 2023, and 2024 Gartner Magic Quadrant™ for Data Integration Tools and top-rated by customers on Gartner Peer Insights, headquartered in San Mateo, California.

At Nexla, our culture is built around our core values:Have Empathy, Be Curious, Be Intellectually Honest, Achieve Excellence, and Remember to Relax. We put our customers at the heart of everything we do, foster a data-driven mindset, take ownership of our work, and believe in the power of teamwork to achieve ambitious goals.

Role, briefly

You would work across the full stack of our SaaS platform: APIs, data models, background jobs, and integrations, writing production Python every day with FastAPI. Nobody hands you a detailed spec. You work with the team to figure out what needs to exist, build it, ship it, and keep it running. Small, focused team, and your work is visible from day one. The API team owns the centralized management plane for all operations on Nexla.

What you’ll own

• Platform features end to end. Data model, API, deployment, and the tests that keep them honest. Production Python every day, mostly FastAPI and SQLAlchemy.
• The APIs the platform runs on, internal services and customer-facing endpoints alike. Performance, reliability, and contracts other teams can build against without asking you first.
• The data layer underneath. Schemas, queries, and migrations across MySQL and Postgres, plus how those models change as the product does. Multi-tenancy and background processing sit here too.
• How your code behaves in production. Debug it, fix it, then build the monitoring and guardrails so that class of problem does not come back. You name the technical debt, performance bottlenecks, and security gaps without waiting to be asked.

Roughly 70% building and shipping, 20% architecture and paying down debt, 10% code review, documentation, and making the people around you better.

Thirty days in: Ship a PR first day, Refactor an existing module first week, Build a feature first month

The hard problem

One thing we're working out right now is a common feature request we get from end-users is the need for dev/staging/production environments for Pipeline building. Building infrastructure for a physical environment deployment in the cloud is too much. Instead, we can build a world-class user experience of environments on our existing setup. The work here requires setting up the right data models in the database and lifecycle management on it with a slick UX.

Must-haves

• 7+ years of professional software engineering, with Python as your primary language. This is a Python role, not a backend role where Python happens to be in the stack.
• FastAPI, or a similar async Python framework such as Starlette, plus SQLAlchemy. You understand async patterns, dependency injection, and ORM tradeoffs.
• Strong SQL and relational database skills. You can design a normalized schema, write a performant query, and reason about indexing and query plans.
• You write unit and integration tests, and you have opinions about what is worth testing.
• You have owned production systems and know what good operational discipline looks like: monitoring, alerting, incident response, post-mortems.
• You use AI tools in your actual work and can say specifically where they help and where they mislead you.
• Working knowledge of AWS or GCP. You have deployed applications, used managed services, and debugged problems below the application layer.
• Background job processing (Celery, Dramatiq, or similar), or message queues and event-driven architectures (Kafka, RabbitMQ, Redis Streams).
• Data-intensive systems, or the data integration domain.

You’ll thrive here if

• You own what you build. You do not wait for permission, and you do not need a finished spec to start.
• You are comfortable defining scope on the fly and shipping before the full picture is clear.
• You would rather fix the class of problem than the instance of it.
• You leave behind enough context and documentation that the team can operate what you built without you in the room.
• You can explain a technical tradeoff to product or leadership without oversimplifying it.

One thing to be clear about: our product definition is still moving as AI reshapes data integration, and the platform has to move with it. If you want a stable, well-defined surface to work on, this is not it.

How we hire

4 conversations, about 2 weeks end to end.

• Coding
• Hiring Manager

On AI in the (coding round): Use it the way you would on the job, ours or anyone else’s. We build AI tooling and we expect you to use AI tooling, so watching you work without it would tell us nothing useful. What we dig into is your judgment: what you delegated, what you verified, and what you threw away.

You will hear from us either way.

The practical stuff

Bengaluru, hybrid, 2 days a week in office. Compensation includes base salary and equity, set by depth and experience rather than by title. You will need to overlap with morning Pacific hours for syncs, design reviews, and collaboration with our US-based leadership and engineering teams.

Why Build Your Future at Nexla? We are standing at the precipice of the GenAI revolution, but the biggest bottleneck isn't the models, it's the data. By joining Nexla, you aren’t just entering a company; you are stepping into the critical layer of the modern data stack that powers the AI economy. We are theData Fabric that enables industry titans like LinkedIn, DoorDash, and J&J to turn messy, siloed data into ready-to-use products for RAG and predictive models. This is your opportunity to move beyond simple tooling and build the actual infrastructure that democratizes data access for the next decade of innovation. If you want to solve the hardest problems in data engineering and own a piece of a market projected to hit billions, your career belongs here.