Salary
≈ $20k – $55k per year (Estimated)
Location
In office (Mumbai)
Seniority
Middle · 3+ years exp
Overview
Company
Impact
Profile match
Adagrad AI is a leading AI solution provider that leverages hardware-accelerated algorithms, enhanced computer vision applications, and advanced tech to develop and deploy scalable solutions for businesses.
We need a versatile engineer - someone who's just as comfortable shipping a backend service as chasing a frontend bug, writing a quick CLI, or prototyping an AI agent. The work shifts week to week, and we need someone who finds that energising rather than chaotic. If you already use Claude Code (or similar agentic tools) as part of how you actually work - not as a curiosity - and you genuinely enjoy debugging Linux systems when things go sideways, we should talk.
Responsibilities:
- Working across the stack - backend, frontend, infra, internal tools, and AI features.
- Using Claude Code and agentic dev tools to ship faster, with the judgment to know when to lean on them and when not to.
- Debugging real problems across services, databases, browsers, and Linux hosts.
- Owning your code through design, ship, monitor, and on-call - not handing it off.
Requirements:
- Bachelor's or higher in Computer Science / IT / Computer Engineering.
- 3+ years of production backend experience with at least one of the following: Python (Django/FastAPI) and solid systems fundamentals (DSA, concurrency, networking, OS).
- Hands-on familiarity with Claude Code (Cursor agents, Aider, Codex CLI, etc. count too).
- Strong Linux fundamentals - shell, processes, networking, systemd, the works.
- Real debugging instincts - stack traces, logs, strace/tcpdump/journalctl, and browser devtools.
- PostgreSQL fluency.
Bonus points if you have:
- Experience in QSR, retail, or similar high-volume operational domains.
- Background in linear programming, optimisation, or demand forecasting.
- Worked with LLM APIs (Anthropic, OpenAI), tool use, evals, and agentic workflow.
- Docker, GCP/AWS, Sentry/Grafana.
- Open-source or internal dev-tooling contributions.
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