STAFF SOFTWARE ENGINEER

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

Responsibilities Include:

● Architecting, building, testing, and deploying applications that support our transportation network

● Modifying designs and specifications of complex applications

● Collaborating and adding value through participation in peer code reviews, providing comments and suggestions

● Leverage AWS and other cloud technologies to design and implement systems in a serverless and event-driven environment

● Working with technical and non-technical end-users, other engineers, and product managers in a cross-functional, quick-moving, and collaborative environment

● Analyzing code, requirements, system risks, and software reliability and providing recommendations on how to leverage our technology more efficiently

● Working with Product and Design to confirm requirements, prioritization, and development of new features

● Design and implement LLM-powered features to solve complex logistics challenges, automate manual operational workflows, and unlock new efficiencies for our network.

● Champion AI-assisted engineering practices by integrating machine learning and intelligent automation into our CI/CD pipelines to predict deployment risks and accelerate delivery cycles.

What You Bring:

● Ability to adapt to changing requirements and work in a fast-paced environment.

● Ability to work effectively in a cross-functional team environment.

● 7+ years of experience building, testing and deploying applications in high-traffic production environments

● 7+ years of experience developing software with Javascript, Node.js and React

● Enjoys taking initiative, is a self-starter, willing to move fast and ship quick, and is excited about collaborating on big challenges

Preferred Qualifications:

● Experience in transportation, logistics or network orchestration systems is highly desirable

● Experience working in a remote first environment.

● Proficiency with AWS, GCP, or similar cloud platforms.

● Strong skills in React and Node.js for end-to-end development. 

Full-Stack Engineer (AI-Native) | 2-4 Years Experience

About the Role

We're hiring a Full-Stack Engineer who is equally comfortable building a polished Next.js interface and a reliable NestJS API behind it. You'll build customer-facing products, including AI-powered features like chat interfaces, streaming responses, and agent-driven workflows. You'll own features end to end, from database schema to UI, and use AI tools daily to ship faster without lowering the quality bar.

What You'll Do

Frontend

• Build responsive, accessible, high-performance UIs with React, Next.js (App Router, RSC) and TypeScript
• Build AI-facing interfaces: streaming chat UIs, tool-call/agent-status displays, and loading, error, and retry states for non-deterministic outputs
• Monitor web vitals and fix performance regressions

Backend

• Design and build scalable REST/GraphQL APIs and services with Node.js and NestJS
• Model, query, and optimize data in PostgreSQL (schema design, indexing, migrations) using an ORM like Prisma or Drizzle
• Implement auth, authorization, validation, background jobs, queues, and caching (Redis)
• Integrate LLM APIs (OpenAI, Anthropic, Gemini), including streaming (SSE/WebSockets), tool calling, retries, rate limits, and cost/latency control

AI-Assisted Engineering

• Use AI coding tools (Cursor, Claude Code, Copilot, etc.) for scaffolding, refactoring, debugging, and test writing
• Write and maintain project context for AI tools (rules files, AGENTS.md/CLAUDE.md, reusable prompts) so the whole team gets better output
• Review AI-generated code critically for correctness, security, performance, and maintainability

Team and Delivery

• Write unit, integration, and E2E tests, using AI to speed them up rather than skip them
• Take part in code reviews, sprint planning, architecture discussions, and on-call/incident follow-ups
• Document APIs, decisions, and runbooks clearly

Must-Have (Non-Negotiable)

Frontend

• Strong JavaScript (ES6+) and TypeScript
• React (hooks, state management, rendering behavior) and Next.js (App Router, SSR/SSG/RSC)
• HTML/CSS fundamentals, Tailwind or similar, responsive design, and accessibility basics

Backend

• Production experience with Node.js and a structured framework (NestJS preferred; Express/Fastify with good architecture is fine)
• Solid PostgreSQL skills: relational modeling, joins, indexes, transactions, query optimization
• API design: REST principles, pagination, versioning, error handling, input validation
• Authentication and authorization (JWT, OAuth2, sessions, RBAC)

Engineering Fundamentals

• Git, PR workflows, and code review habits
• Testing across layers (Jest/Vitest, React Testing Library, API/integration tests; Playwright/Cypress is a plus)
• Basic security awareness (OWASP top 10, secrets management, input sanitization)

AI-Assisted Development

• Daily, hands-on use of at least one AI coding tool (Cursor, Claude Code, Copilot, Windsurf, or similar)
• Ability to write clear prompts, give useful context, and break big tasks into steps an AI can handle
• Habit of reviewing, testing, and understanding AI output before committing it
• Basic understanding of how LLMs work: context windows, hallucinations, token cost, and why outputs vary

Nice to Have

• Redis, message queues (BullMQ, SQS, Kafka), or event-driven architecture
• Monorepo tooling (Turborepo, pnpm workspaces, Nx)
• Design system or component library work (shadcn/ui, Radix, Storybook)
• tRPC, GraphQL, or OpenAPI-driven type-safe clients
• Multi-tenant SaaS, payments (Stripe/Razorpay), or real-time features
• Open-source contributions, a side project, or shipped AI features you can demo

What We Expect From You

• Ownership: take a feature from schema to UI to production, and flag risks early
• Judgment over speed: AI makes you faster, and you're still accountable for every line you ship
• Security awareness: no secrets in prompts, no blind copy-paste of AI code, and sensitive data stays out of third-party tools
• Systems thinking: consider scale, failure modes, and cost, not just the happy path
• Learning speed: the AI tooling landscape changes every few months, and you keep up and share what works
• Clear communication: PRs, docs, and async updates that others can follow

If interested for this job pls contact us on this WhatsApp number, nine three one six one two zero one three two

Role: Full Stack JavaScript/TypeScript Developer

We're looking for a Full Stack Developer with strong JavaScript/TypeScript fundamentals to join our team and help build AI-powered product features.

Responsibilities:

Core Skills & Competencies (Must have):

• Strong proficiency in TypeScript and solid JavaScript fundamentals
• Front-end development skills with the React ecosystem (Next.js), including state management libraries like Zustand, Redux
• Expertise in HTML/CSS, with experience creating responsive and adaptive designs
• Experience building AI-assisted features such as chatbots, content generation, semantic search, recommendations, or intelligent automation
• Experience with RESTful services and APIs
• Familiarity with AI SDKs, LLM APIs, and vector databases
• Experience with SQL and database management, understanding relational databases, and ability to write efficient and optimized queries
• Understanding of database design and management, especially with SQL
• Experience with version control systems such as Git
• 
  

Desired Skills & Competencies (Nice to have):

• Experience with event-driven architecture
• Experience with cloud services like Azure or AWS
• Familiarity with modern DevOps practices
• Understanding of security practices and web application security
• Familiarity with CI/CD pipelines
• 
  

What we're looking for:

• Strong command over JS/TS fundamentals, not just framework-level knowledge
• Candidates with internship experience or a background from a reputed engineering college preferred
• Please share your GitHub link, portfolio, or details of projects you've built (personal, academic, or professional)

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

About the Role

Pendo is looking for a Staff Software Engineer to lead teams building core product capabilities across Analytics, Guides, and Platform services. These are the systems that power how hundreds of millions of end users experience the software.

In this role, you will drive execution against business objectives, direct complex initiatives from kickoff through delivery, and build a team that operates with clarity and focus. You will set clear expectations, delegate effectively, and partner closely with product, design, and senior engineering leadership to keep teams aligned and moving. You default toward action, push teams to deliver value daily, and actively use AI tools as part of how you work.

If you're energized by directing high-impact teams, developing strong engineers, and building a culture where craft and velocity coexist, this role is a great fit.

What You'll Do

Team Leadership & Hiring

• Create an environment where engineers are encouraged to take risks, experiment, and challenge the status quo.
• Lead, mentor, and grow a team of engineers through clear expectations, coaching, and timely feedback.
• Own hiring end-to-end, partnering with recruiting to attract and close top engineering talent.
• Build an inclusive, high-performing team culture grounded in ownership, accountability, and continuous improvement.

Delivery & Execution

• Maintain a high bar for velocity, predictability, and quality.
• Own team execution against product and engineering goals.
• Partner with Product and Design to define roadmaps, scope work, and deliver high-quality outcomes.
• Identify and remove blockers, manage risks, and ensure strong planning and prioritization.

Cross-Functional Collaboration

• Work closely with product, design, infrastructure, and other engineering teams to deliver cohesive customer experiences.
• Align team priorities with broader organizational goals and strategy.

Operational Excellence

• Drive improvements in system reliability, performance, and scalability.
• Establish strong practices around monitoring, incident response, and continuous improvement.

What We're Looking For

• 8+ years of experience in software engineering.
• 3+ years of experience managing and growing engineering teams.
• Proven track record of hiring and building high-performing teams.
• Experience delivering complex, cross-functional initiatives in a product-driven environment.
• Strong technical foundation in backend, distributed systems, or full-stack development.
• Proven ability to lead teams through ambiguity and change while maintaining execution.
• Actively uses AI tools in day-to-day work and helps drive adoption across teams.
• Strong communication, organizational, and stakeholder management skills.

Nice to Have

• Experience working on analytics products, user-facing SaaS platforms, or data-intensive systems.
• Experience managing teams across both frontend and backend domains.
• Familiarity with modern cloud environments and scalable architectures.
• Experience working in distributed teams across multiple time zones.

Position: Senior/Lead Full Stack Engineer – Gen AI / Agentic AI

Experience: 7+ Years

Employment: Permanent Position

Location: Banglore / Hyderabad

Job Summary

We are looking for a Senior/Lead Full Stack Engineer – Gen AI / Agentic AI with strong hands-on experience in Python, React.js, MongoDB, Java/Spring Boot and Generative AI/Agentic AI.

The candidate should have experience designing and developing scalable enterprise applications and implementing production-grade LLM, RAG, AI Agent and multi-agent solutions.

Key Responsibilities

• Design, develop and maintain scalable full-stack applications using Python, React.js, MongoDB and Java/Spring Boot.
• Build production-grade Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
• Develop RAG pipelines, AI agents, tool calling, memory management, planning and agent orchestration.
• Work with LangChain, LangGraph, MCP, vector databases and semantic search.
• Develop Python-based APIs, microservices and asynchronous applications using FastAPI/Flask/Django.
• Build REST APIs and event-driven microservices with focus on scalability, performance and resilience.
• Integrate LLMs, embeddings, vector stores and external enterprise tools/services.
• Implement prompt engineering, LLM evaluation, guardrails and AI observability.
• Develop responsive front-end applications using React.js.
• Work with MongoDB, SQL and hybrid data models.
• Implement CI/CD pipelines and support cloud/OCP deployments.
• Follow secure coding, testing, code quality and performance best practices.
• Participate in architecture, technical design, code reviews and mentoring of team members.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.

Mandatory Skills

1. Python
2. React.js
3. Gen AI / Agentic AI
4. RAG + LLM
5. LangChain / LangGraph
6. MongoDB
7. Java + Spring Boot
8. REST APIs / Microservices
9. Vector Databases / Embeddings
10. MCP / AI Agent orchestration

Good to Have

• FastAPI / Flask / Django
• Kafka / Solace
• Docker / Kubernetes
• AWS / Azure / GCP / OCP
• CI/CD – Jenkins / GitHub Actions
• LLMOps / AI evaluation / observability
• ELK / Grafana / Splunk / AppDynamics
• SQL / NoSQL
• Agile/Scrum

Role- Sr Senior Engineer 

Location -Hyderabad 

Shift -Night Shift starts from 8:30 PM IST 

About The Role

As a Senior Engineer on the team, you will own systems end to end across a high-volume, event-driven surface. You'll build the APIs and services behind key initiatives including:

- The driver comms platform — the rules engine, cohorting, and scheduling that reach drivers across SMS, push, and email

 - The onboarding funnel and applicant tracking layer, architected to support Veho's move to an in-house system over time

 - Live selling workflows that turn live offer and market-clearing data into well-timed, well-targeted driver outreach

You'll partner closely with Product, Design, Operations, and Data Science to ship tooling that scales with Veho's growth.

Responsibilities Include:

- Design, build, test, and deploy features across the driver-facing apps (driver mobile app, onboarding and registration surfaces), our GraphQL APIs, and the event-driven services behind them

 - Own a problem end to end: write the design doc your team works from, build it, roll it out behind a feature flag, and stay on it after launch until it is stable

 - Own the driver comms platform — the rules engine, cohorting, and scheduling that decide when to reach a driver over SMS, push, or email, and the delivery services behind it

 - Build the onboarding funnel and applicant tracking layer: registration and set-password flows, consent and eligibility gating, and the integrations that track where every applicant sits in the funnel

 - Build live selling workflows that consume live offer data and market-clearing signals to notify the right driver cohorts only when routes are actually claimable

 - Contribute to architectural decisions and technical design for complex, distributed systems, and architect today's comms and onboarding infrastructure so it supports the eventual in-house replacement of our third-party ATS rather than becoming throwaway work

 - Break a project into milestones your product, design, ops, and data partners can plan against

 - Write correctness-first code in an event-driven system where delivery is at-least-once and no driver may be texted twice about the same route — and where a send must never fire when there is no offer to claim

 - Improve reliability and observability in the services you own, with alerts that fire on real problems and stay quiet otherwise, so an on-call engineer is paged for a broken send pipeline and not for noise

 - Propose the engineering work your team should be doing, including the reliability, data-quality, and compliance work nobody is asking for

 - Use AI-native development workflows and tooling (Claude Code, Cursor, Copilot, and similar) as part of how you ship

 - Mentor the engineers around you, keep the team's code review bar high, and write down what you learn

What You Bring:

- 5–7+ years of experience building, testing, and deploying applications in high-traffic production environments

 - Depth in AWS serverless, including Lambda, a managed GraphQL layer such as AppSync, DynamoDB, EventBridge, and SQS

 - Experience with event-driven systems and the idempotency work that comes with at-least-once delivery — especially in a comms context where duplicate or misfired messages reach real people

 - Strong full-stack experience with TypeScript, Node.js, GraphQL, and React

 - Experience with DynamoDB single-table design

 - Experience integrating with third-party platforms and their webhooks, and keeping the data they produce in sync and trustworthy across services

 - At least one project owned through production rollout, including what broke afterward and who fixed it

 - Experience operating a service in production long enough to own its failure modes

 - Judgment about what a design costs in engineering time, dollars, and vendor commitment

 - A self-starter mindset with the ability to move quickly and ship iteratively, including on migrations, compliance obligations, and the manual steps nobody has automated yet

 - Enthusiasm for working closely with product, design, operations, data science, and support partners

-Tech Stack: AWS, TypeScript, Node.js, React, React Native, GraphQL, DynamoDB, serverless event-driven architecture; 

multi-channel comms (SMS, push, email); Firebase Auth; Statsig for experimentation; Redshift/Databricks-backed data pipelines

Preferred:

 - Experience with applicant tracking / recruiting funnels or other funnel-driven onboarding systems, and the drop-off analysis that improves them

 - Experience with experimentation and analytics infrastructure (Statsig, Fivetran, Redshift, Databricks) to measure and tune what you ship

 - Consent modeling and compliance obligations (e.g., driver terms-and-conditions and messaging consent) that span services

Total Experience: 4+ years

Mode of Hire: Permanent

Required Skills Set (Mandatory): HTML, JavaScript, Node.js, Express.js, MongoDB, React/Next.js, AI Integration (LLMs/APIs - OpenAI, Anthropic, Gemini)

Desired Skills (Good if you have): Cloud Platforms (AWS), System Design, Application Security

What is the role all about?

We're hiring full-stack engineers who build with AI, not the traditional way. You should be fluent in modern web engineering, primarily Node.js, and just as fluent in using LLMs and AI tools (Cursor, Claude Code, and similar) to ship fast. Work that once took a month should take a week; what took a week should take a day.

The role spans a range, from architecting backends for non-trivial products like assistants and agents, to rapidly turning a requirement into a clean, customer-facing app or MVP. Be strong in at least one area, be comfortable across the system as a whole, and tell us where you're strongest so we can place you accordingly.

What will you do?

• Plan, build, and ship product features end-to-end, with AI embedded where it has the most impact.
• Integrate LLMs and AI APIs into production-grade applications.
• Use AI tools to prototype, build, and deliver at high speed without sacrificing quality.
• Design scalable APIs and data models with Node.js, Express.js, and MongoDB.
• Build responsive, performant, customer-facing interfaces with React/Next.js.
• Contribute to design discussions, code reviews, and architectural decisions.

What are we looking for?

AI leverage: 

• You've shipped real things using LLMs or AI APIs and instinctively reach for AI to move faster. 
• Comfortable with prompt engineering and judging AI output for production-readiness.

Engineering depth and delivery:

• Solid fundamentals: problem-solving, data structures, and how systems fit together. 
• At least 2+ years across frontend (React/Next.js), APIs (Node.js/Express.js), and databases (MongoDB). 
• You write clean, production-grade code and you ship.
• Knowledge of application security or ethical hacking is an advantage.

Culture

• Work with performance-oriented teams driven by ownership and passion.
• Learn to design systems for high accuracy, efficiency, and scalability.
• No strict deadlines, focus on delivering quality work.
• Meritocracy-driven, candid culture. No politics.
• Very high visibility regarding which startups and markets are exciting globally.

About Tracxn

Tracxn (Tracxn.com) is a Bangalore-based product company that provides a research and deal-sourcing platform for Venture Capital, Private Equity, Corp Dev, and professionals in the startup ecosystem.

We are a team of 800+ working professionals serving customers across the globe. Our clients include Funds such as Andreessen Horowitz, Matrix Partners, and GGV Capital, as well as Large Corporates such as Citi, Embraer & Ferrero.

Founders

• Neha Singh (ex-Sequoia, BCG | MBA - Stanford GSB)
• Abhishek Goyal (ex-Accel Partners, Amazon | BTech - IIT Kanpur)

About Technology Team

Tracxn's Technology team is 50+ members strong and growing. The technology team is subdivided into multiple smaller teams, each of which owns one or more services/components of the technology platform. Ours is a young team of motivated engineers with a minimal management structure, in which almost everyone is actively involved in technical development and design. We have a team-centric culture where ownership and responsibility for a feature or module lie with a team rather than an individual.

We work on an array of technologies, including but not limited to ReactJS, Next.js, Storybook, Webpack, Node, Mongo, AWS Lambda, Spring, Elastic Stack, MySQL, Kafka, Redis, Ansible, etc.

We value ownership, continuous learning, consistency, and discipline as a team.

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.