AI Product Engineer
Senior · Ahmedabad or remote within India · Full-time
gStride AI is hiring a Senior AI Product Engineer to ship productivity intelligence features end-to-end. We are a four-person AI-first product team building productivity intelligence for mid-market teams. We read what teams ship — not how they type.
Apply: email hello@gstride.ai · book 15 minutes with Ashok · DM on LinkedIn.
Why this role exists
gStride AI is a four-person product team building AI productivity intelligence for mid-market teams. We read what teams ship, not how they type. The AI Product Engineer pod is two senior engineers who own vertical-slice features end-to-end. Roadmap items — focus mosaic scoring, recommendation engine, audit-trail ML, anomaly detection — are queued behind engineering capacity. That is what this hire fixes.
You join the pod as the third engineer. You become a peer of two senior engineers, paired directly with the AI Product Lead on architecture, and you ship product surface features that customers use within one to three weeks of writing them.
If you have been waiting for a role where AI is the substrate of the work rather than a feature bolted onto a SaaS, this is that role.
What you will do
- Ship end-to-end AI features in 1–3 week vertical slices: data pipeline, model, API, product surface.
- Wire LLM-augmented workflows into the product — focus-mosaic scoring, recommendation generation, anomaly detection.
- Build the audit-trail layer. Every AI score must be reproducible to source events. The explainability and rule-trace stack from Pillar five is your home.
- Own ML eval pipelines: golden-dataset labeling, inter-rater agreement, A/B harnesses, regression gates.
- Work directly with Ashok on product specs. No PM layer.
- Co-design integrations with the four-layer architecture: Capture, Signal, Recommendation, Action.
- Ship a feature every two to three weeks. Cadence is measured in PRs merged, not lines of code.
- Dogfood the product. gStride runs on gStride internally — your dashboards include you.
What we expect
- 4–7 years software engineering experience. Python or TypeScript or Node.js as your primary stack.
- At least one production ML or AI feature you shipped end-to-end — not just notebooks, not just Kaggle.
- Strong fundamentals: SQL, system design, API design, data modeling.
- LLM-fluent. Comfortable with prompt engineering, RAG, agent workflows, and evaluation.
- Comfort with the Azure stack. We run on Azure Static Web Apps and Azure Functions plus Azure AI services for enterprise tenants.
- Anti-surveillance and privacy-first values alignment. No fence-sitters on the positioning.
- Native or near-native English. Bonus: Hindi or Gujarati for local team flow.
- Strong written voice. We ship docs as much as code.
- Comfortable with founder-led ambiguity. We will move the goalposts more than once a quarter.
The stack we run
- Frontend: Vue 3 (static HTML plus Vue components) on Azure Static Web Apps.
- Backend: Node.js Azure Functions today; Python ML services on the roadmap.
- Data: PostgreSQL plus Redis cache. HNSW vector index via AgentDB for semantic search.
- AI: Anthropic Claude as primary, OpenAI as fallback, Azure OpenAI for enterprise tenants.
- Tooling: Claude Code, Cursor, GitHub Copilot — we use all three depending on workflow.
- Observability: GA4, Microsoft Clarity, custom event log.
What you get
- INR 25–50L base salary plus ESOP grant. Final offer indexed to seniority and last comp.
- Ahmedabad office or remote-flexible within India.
- Direct founder access. No middle layer between you and Ashok.
- Real product ownership. Your code ships to all customers.
- AI-augmented every workflow. Claude Code, Cursor, Copilot, and internal tooling on tap.
- Health insurance to Indian standard.
- Conference and learning budget — currently 50K INR per year.
What we do not want
- Anyone who treats AI as wrap-an-LLM-around-it.
- Process-for-process engineers. We do not run scrum theatre.
- Fence-sitters on the anti-surveillance positioning.
- Notebook-only ML. We ship to production, not to Kaggle leaderboards.
- Anyone uncomfortable with directly-typing-with-Claude-Code culture.
How to apply
- Email hello@gstride.ai with subject "AI Product Engineer — your name".
- Include 2–3 sentences on why this role, your LinkedIn URL, and one GitHub link to AI or ML production work you shipped.
- If it clicks, book 15 minutes with Ashok at cal.com/ashok-sachdev/15min. The process from there is two short steps.