Lead Full Stack AI Engineer

Sahaj Software

Austin (TX)

On-site

USD 150,000 - 240,000

Full time

14 days+
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Job summary

Sahaj Software is seeking a highly experienced engineer for a deeply technical Lead Engineer role, translated internally to Solution Consultant. The work centers on building data-heavy, distributed systems and AI-powered software with near-constant coding presence.

The position emphasizes deep engineering impact, minimal process, and ownership across a global product footprint, including production-grade AI integrations and scalable architectures.

Qualifications

  • Applicants must be a Green Card holder (Permanent Resident).
  • We are unable to transfer/sponsor new H-1B visas or accept applicants who require future visa sponsorship.
  • We are also unable to consider candidates currently on OPT even if you have started the H-1B process.

Responsibilities

  • Design and build systems that deal with real-world complexity (not toy problems).
  • Write production code frequently, not just review or direct.
  • Build services and applications that interface with modern AI stacks - model APIs, embeddings, vector databases and other AI capabilities.
  • Ship robust, production-level AI-powered systems.
  • Work across languages when needed, not just your comfort zone.
  • Break down messy problems into clean, maintainable systems.
  • Push back on bad ideas, including ours.
  • A “review-only” architect.
  • Someone removed from the code.
  • Someone whose job is primarily model training or ML research.

Job description

Due to the nature of work with our client, applicants must be either:

  • Green Card holder (Permanent Resident)

Unfortunately, we are unable to transfer / sponsor new H-1B visas or accept applicants who require future visa sponsorship. We are also unable to consider candidates currently on OPT even if you have started the H-1B process.

role = "Lead ENGINEER" if raises_bar(team) and depth >= LEGENDARY and ships_code else "SENIOR"
Let’s decode this

We're not just looking for someone who has "been around for 10+ years". We're looking for someone who has raised the bar for in backend or full-stack engineering for 10+ years.

  • raises_bar(team) → The people around you write better code because you are there. You mentor through pairing and feedback, not hierarchy.
  • depth >= LEGENDARY → You have gone deep enough to hold strong opinions, and humble enough to change them.
  • ships_code → You still build. Regularly. In production.
This role isn’t for everyone

It’s for engineers who want to stay close to the code, go deep, and build software where AI is becoming part of the system.

What the work looks like

We can't promise which problem you'll pick up, but the menu right now looks something like this:

  • Redesign a ClickHouse schema so an ad buyer can query 85 billion rows in under two seconds, and discover that pre-exploding the rows 168x is actually the right answer.
  • Keep a vehicle telemetry platform moving billions of messages a day without the Kafka consumers falling over.
  • Build the engineering spine of a mobile wallet used by more than two billion people across four continents.
  • Ship the data product behind peer-review submissions for one of the world's largest scientific publishers.

The list changes. The pattern doesn't: data-heavy, distributed, and often sitting on top of something that already exists and isn't perfect.

What you will actually do
  • Design and build systems that deal with real-world complexity (not toy problems)
  • Write production code frequently, not just review or direct
  • Build services and applications that interface with modern AI stacks - model APIs, embeddings, vector databases and other AI capabilities
  • Ship robust, production-level AI-powered systems
  • Work across languages when needed, not just your comfort zone
  • Break down messy problems into clean, maintainable systems
  • Push back on bad ideas, including ours
  • A “review-only” architect
  • Someone removed from the code
  • Someone whose job is primarily model training or ML research
How we think about engineering
  • Code that is simple, testable, and built to change
  • Engineers who can explain their design decisions clearly
  • TDD, refactoring, and continuous improvement - not as rituals, but as tools
  • Choosing the right technology, not the fashionable one
  • Software engineers who understand AI - not necessarily ML researchers who happen to write software
We don’t care much about:
  • Framework loyalty
  • Whether you’ve used our exact stack before
Tech (context, not a checklist)

You don't need to have shipped all of these. You do need the ability to learn what the problem demands.

What you’ll get
  • A place where Lead Engineers still write code - daily
  • One designation across the company: **Solution Consultant**. "Lead Engineer" is just the translation for the outside world
  • Small teams, high ownership, large impact, minimal process overhead
  • No reporting managers. Decisions happen where the code does
  • Find your balance between work and life’s ups and downs with unlimited leave when you really need it
  • **Open salaries.** Inside Sahaj, every Sahajeevi can see every other Sahajeevi's pay, including the founders'. The annual hike is voted on collectively in a room where the whole company reads the P&L
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