Build production AI integrations at the edge of the practice.

What it’s like to work here

We’re a small senior team operating across India and the United States. Most of the engineering happens out of Visakhapatnam; client-facing work and time-zone-overlap work happens out of Stanford, California. We’ve been in production software since March 2006 — what changed in the last three years is that we now apply that discipline to integrating AI into the systems funded businesses already run.

You’ll work on real production AI integrations — into CRM systems (HubSpot, Salesforce, Zoho), email platforms, support tooling, document workflows. Real client data, real users, real consequences if it breaks. The work is varied because every client’s stack is different. The throughline is engineering discipline applied to a domain most teams are still figuring out.

What you won’t do here

• Long discovery engagements that never ship. We sell 30-day proof-of-value engagements. That means three weeks of building, one of measuring, every single time. Nothing sits in slideware.
• Bench rotation between unrelated tickets. You own an integration end-to-end. Architecture, build, observability, hand-back. That ownership is part of the job design.
• Wrap deliverables in fake AI buzzwords. If AI isn’t the right answer for a workflow, we say so. Internal honesty is the only way the practice keeps its credibility outside.

Roles we hire

We don’t always have an open job listed. We always read inbound from senior engineers. Roles we’ve hired most often:

Senior AI Integration Engineer

You’ll own integrations of AI into client CRMs, email platforms, and document workflows. Comfortable with at least one major LLM SDK (Claude, OpenAI, Bedrock), one major CRM (HubSpot, Salesforce, or Zoho via API), and one cloud (AWS, Azure, or GCP). You read evals, you build observability into systems before shipping them, you know how to control token cost. You can talk to a client’s VP of RevOps without an intermediary.

Senior Full-stack Engineer

You build the surfaces our AI integrations live in — dashboards, admin panels, embedded widgets, internal tools. Strong on at least one modern frontend framework (React or Vue) and one backend (Node, PHP, or Python). You care about the user the same way the AI engineer cares about the model.

Senior DevOps / Reliability Engineer

You make sure what we ship stays shipped. Observability, audit logging, cost budgets with hard caps, deployment automation. Comfortable across at least two clouds. You’ve been on-call for a real production system and have opinions about it.

Solutions Engineer (US-based)

You sit between the client’s reality and our engineering. You scope 30-day engagements, write honest proposals, and stay close enough to delivery to keep promises honest. Engineering background required — this isn’t a sales role.

What we look for, in any role

• Production track record. Years matter less than scars. We want people who have shipped systems that paying users depended on.
• Comfort with AI as a tool, not a religion. You use it, you understand its failure modes, you don’t oversell what it can do.
• Engineering writing. We write a lot — design docs, post-incident notes, proposals, client-facing briefs. You can write a clear paragraph that an engineer in a different time zone can act on.
• Asynchronous discipline. Half the team is twelve hours ahead of the other half. We don’t do daily stand-ups; we do tight written hand-offs.
• Respect for the client’s business. We don’t come in to teach them their job. We come in to add a capability to a business they built without us.

How we work

Time and location

Remote-first across both offices. India team works from Visakhapatnam (some come into the office, some don’t). US team is in / near the Bay Area. We don’t require relocation for hires in either geography. We’re open to senior hires in other geographies on a case-by-case basis if there’s a strong fit.

Compensation

Senior market for the geography you work from. We’re a profitable services business, not a venture-backed startup — we pay in salary, not equity lottery tickets. Variable component tied to delivered engagements, not vague KPIs.

Learning

The AI integration field is changing fast and we don’t pretend to know everything. Budget for conferences, model API costs for experimentation, and dedicated “reading time” for new papers and tools. We expect you to share what you learn with the rest of the team.

How to apply

Email [email protected] with:

• A short note (one or two paragraphs) on what you’ve shipped recently and what you’d want to ship next
• A CV or LinkedIn link
• The role(s) above that fit — or tell us where you’d fit if the list doesn’t cover it
• Optionally: a link to a piece of writing (blog post, internal doc you can share, RFC) so we get a sense of how you think

We read everything. Replies typically come within one week. If we’re a fit we’ll move into a short technical conversation; if not we’ll tell you honestly.

Questions we get

Do you sponsor visas?+

For the US office, case-by-case for senior roles. For India, we hire candidates who are eligible to work in India. We’ll be upfront about it before we get deep into the process.

What does your interview process look like?+

A short async portfolio review (read your CV / writing / repos), then one technical conversation (60-90 minutes, real work, no leet-code puzzles), then a chat with the founder. Three steps total. We aim to give a decision within ten working days.

Are you hiring juniors or interns?+

Not at the moment. We put senior engineers on client production AI systems — that’s a deliberate part of how we run, not a stage we’ll grow out of. If you’re early-career and want to work in this space, we’d encourage you to build something real and come back.

I don’t see a role I match. Should I still apply?+

Yes — especially if you have a track record we’d recognise (production AI work, large-scale CRM/email/support engineering, an unusual specialty that’s adjacent to what we do). The role list above is a pattern, not a ceiling.