Staff / Principal Engineer (Full Stack)

Bengaluru, hybrid

Location: Bengaluru (Hybrid) | Experience: 6 to 12+ years | Compensation: Competitive cash compensation + significant ESOPs with meaningful long-term upside

About ResultFlow.ai

At ResultFlow.ai, we build AI that helps ecommerce stores convert more of their visitors into customers. Merchants add our JavaScript plugin to their site, and our AI runs experiments and personalises their pages automatically, carrying learnings from one store to the next. It is a genuinely hard problem that spans frontend, backend, data, and LLM systems, all running on real, live stores where correctness matters.

We are a small, fast-moving team that makes decisions with data and ships quickly. We are looking for an experienced Staff, Senior Staff, or Principal Engineer to own significant parts of our product and raise the bar for how we build. The exact level will depend on your technical depth, breadth, and the scale of problems you have independently owned.

The role

This is a hands-on, individual-contributor role. You will be in the code every day. We leverage agentic coding to ship maximum code. Your role is not management, it is individual contribution. What sets it apart from a senior role is scope: you will own a whole area of our product rather than a set of individual tasks, take significant and often ambiguous problems from idea to shipped system, and pull other engineers along with you as you go.

You will work across the full stack: frontend that runs on third-party sites, backend APIs and integrations, data at scale, and LLM-powered systems. You will make the architectural calls within your area, and you will be someone the team relies on to turn a fuzzy problem into a working result.

What you will do

Own a system or area of the product end to end, including the messy, ambiguous parts that do not come with clear instructions.
Make sound design and technical decisions within your domain, and explain and defend the trade-offs.
Take vague business or product requirements, shape them into a clear technical plan, and execute.
Care about how your systems behave in production: correctness, performance, and maintainability over time.
Raise the level of the engineers around you through how you build, review, and think, without managing them.

What we are looking for

6 to 12+ years of professional software engineering experience.
A track record of owning projects or systems that span multiple components, not just building individual features inside someone else's design.
Deep, hands-on strength across most of the stack:
- Frontend: strong understanding of how the browser works (rendering, the DOM, the event loop, networking, performance).
- Backend: strong command of a language such as Python or Java, with solid experience in API design, authentication, and third-party integrations.
- Deployment: comfortable deploying and operating systems, on a VPS or via orchestration such as ECS or Kubernetes.
- Data: experience with data warehouses and data at scale.
- ML and LLMs: a solid grasp of core ML concepts and hands-on experience building with LLM APIs, including their parameters and failure modes.
- Ownership and judgment: you take responsibility for outcomes, make sound calls under ambiguity, and make the team better.

The mindset we value across the whole team: data-driven, questioning, strong opinions held loosely, a fast and deep learner, a sense of urgency, and clear communication.

A strong plus

Experience with experimentation systems, A/B testing or bandit methods, personalisation, or data instrumentation pipelines. This is the core of what we do.
Experience working with data-intensive and infrastructure systems beyond typical full-stack application development — for example, data warehouses or analytical databases such as ClickHouse, caching and distributed systems such as Redis, queues/streaming systems, and the infrastructure required to operate them reliably at scale.
Comfortable going beyond application code when needed: understanding databases, networking, containers, cloud infrastructure, observability, performance bottlenecks, and production debugging rather than treating infrastructure as someone else's responsibility.

How our process works

Our hiring is work-first. If you progress, you will complete a practical task and then discuss it with us in depth, including your design and technical decisions, so we can see how you actually think and build. Using AI tools is welcome throughout, as long as you understand and can explain everything you produce.

Name *

Email *

Have you deployed and owned the backend in AWS/Azure/GCP etc. Please explain *

Have you setup a github project for a team from scratch, what are the things you did. Please explain *

Have you tried making any RAG or agentic apps based on LLM apis. Please explain. *

Have you worked with Datawarehouses or ETL or what you know of it *

What's your favourite book or course *

What are some caching related working you had done in your work *

LinkedIn profile *

Phone *

Latest date of joining *

Github *

Years of experience *

Made withBinary

About ResultFlow.ai

The role

What you will do

Own a system or area of the product end to end, including the messy, ambiguous parts that do not come with clear instructions.

Make sound design and technical decisions within your domain, and explain and defend the trade-offs.

Take vague business or product requirements, shape them into a clear technical plan, and execute.

Care about how your systems behave in production: correctness, performance, and maintainability over time.

Raise the level of the engineers around you through how you build, review, and think, without managing them.

What we are looking for

6 to 12+ years of professional software engineering experience.

A track record of owning projects or systems that span multiple components, not just building individual features inside someone else's design.

Deep, hands-on strength across most of the stack:

Frontend: strong understanding of how the browser works (rendering, the DOM, the event loop, networking, performance).
Backend: strong command of a language such as Python or Java, with solid experience in API design, authentication, and third-party integrations.
Deployment: comfortable deploying and operating systems, on a VPS or via orchestration such as ECS or Kubernetes.
Data: experience with data warehouses and data at scale.
ML and LLMs: a solid grasp of core ML concepts and hands-on experience building with LLM APIs, including their parameters and failure modes.
Ownership and judgment: you take responsibility for outcomes, make sound calls under ambiguity, and make the team better.

The mindset we value across the whole team: data-driven, questioning, strong opinions held loosely, a fast and deep learner, a sense of urgency, and clear communication.

A strong plus

Experience with experimentation systems, A/B testing or bandit methods, personalisation, or data instrumentation pipelines. This is the core of what we do.

Experience working with data-intensive and infrastructure systems beyond typical full-stack application development — for example, data warehouses or analytical databases such as ClickHouse, caching and distributed systems such as Redis, queues/streaming systems, and the infrastructure required to operate them reliably at scale.

Comfortable going beyond application code when needed: understanding databases, networking, containers, cloud infrastructure, observability, performance bottlenecks, and production debugging rather than treating infrastructure as someone else's responsibility.

How our process works