Lead Software Engineer / Architect — Agentic AI Platform at Juliet AI, Inc. · Remote only · 7 - 12 years · ₹40L - ₹70L / yr (ESOP available) · Bootstrapped · Remote only · Posted 5 Sep 2026

Experience: 8+ years, senior candidates only | Type: Full-time | Location: Remote (India)
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WHAT WE'RE BUILDING
We're building Juliet, an AI that runs marketing end to end. Our users are marketers, founders, CEOs, growth leads, agencies, and SMBs — not developers. They
tell Juliet the goal. She plans, writes production code, and ships real marketing: conversion-optimized websites, launch assets, campaigns, audits, autonomously.
That's the engineering problem in one line: the humans in the loop can't read code, so the agent has to get it right on her own — plan, build, self-correct,
recover, ship.
Under the hood: a browser-based studio backed by cloud sandboxes, a real-time SSE streaming pipeline, and a LangGraph agent working across 83 tools and 63 skill
modules. The agent isn't bolted onto the product. She is the product.
Small team, big ambitions. You'll ship things users touch daily, not write tickets about them.
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THE ROLE
We're hiring one architect-level backend engineer to own Juliet's agentic infrastructure end to end. That means the agent graph, the execution environment, the
streaming pipeline, the state and memory systems — and setting technical direction for the engineers working alongside you.
This is a player-coach seat. You'll still write code every day, and your architectural calls become the product. You'll work directly with the founder. No PMs in
between.
Frontend is part of the system. You won't be leading it, but you'll need to understand how the agent's output reaches the browser and be able to ship full-stack
features when needed.
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THE STACK
AI agent (primary): Python 3.11, LangGraph 1.x + LangChain, Anthropic / Google / OpenAI model providers
API (primary): NestJS 11, Supabase, Redis, PostgreSQL, Server-Sent Events
Infra (primary): Modal cloud sandboxes, Docker, Netlify deployments
Frontend (secondary): Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js
Monorepo: Turborepo, pnpm
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WHAT YOU'LL WORK ON
The majority of your time is here:
Agentic AI workflows — Design, extend, and harden the LangGraph agent graph: multi-step planning, code generation, tool dispatch, self-correction, and recovery
across 83 tools and 63 skill modules. This is the core of the product.
Real-time streaming architecture — The SSE pipeline that carries every agent action from the Python backend through NestJS to the browser: event framing,
reconnection, health monitoring, interrupt handling for plan approvals and clarifying questions.
Agent execution environments — Sandbox lifecycle on Modal: container spin-up, file sync, terminal I/O, command execution, and live preview with per-asset esbuild
bundling. The agent lives here.
State and memory systems — LangGraph Postgres checkpointers, middleware-injected context (goals, design docs, memory anchors), conversation summarization. How
the agent knows what it knows.
Backend API and data layer — NestJS services, Supabase schema, Redis caching, quota enforcement, webhook handling. The plumbing the agent depends on.
Marketing intelligence pipelines — AEO, CRO, and brand-perception audit engines: multi-LLM probing, parallel inference, streamed structured reports, result
caching. Audit-at-scale infrastructure.
The remaining ~25% of your time:
Full-stack product features — Collaboration (roles and permissions), the Netlify deployment pipeline, subscription and quota flows, onboarding. You'll ship these
end to end — backend first, frontend to close the loop.
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WHAT WE'RE LOOKING FOR
Must-have:
- 8+ years of professional software engineering, including meaningful time as a tech lead or systems architect who owned something end to end. Closer to ten is
the norm for people who thrive here.
- Both worlds on your resume: engineering rigor inside a large company and 0-to-1 ownership at an early-stage startup.
- Production agentic systems experience. You've built and operated LLM agent systems in production with LangGraph, LangChain, or equivalent — agent graphs, tool
use, state management, prompt engineering, evals. This means well beyond calling a chat endpoint.
- Strong Python. You design and ship production Python daily. The agent codebase is yours to own.
- Architect-level system design. You can own how data flows across four services, make tradeoffs under uncertainty, and defend every call.
- AI-native development workflow. You drive Claude Code, Codex, or similar agentic tools as everyday instruments — not occasionally. You have opinions about
working with coding agents because you do it constantly.
- Real-time backend systems. You've built SSE, WebSocket, or streaming API infrastructure in production — not just consumed it.
- Strong TypeScript. The API layer and most product features are in TypeScript. You're productive in it.
Strong plus:
- Background in developer tools, IDEs, or coding/execution platforms
- Container runtimes and sandboxed execution (Modal, E2B, Firecracker, or similar)
- Depth in PostgreSQL, Redis, and Supabase
- LLM observability and evals tooling (LangSmith or similar)
- NestJS or equivalent Node.js API framework experience
- React/Next.js — enough to ship a full-stack feature without handoff
- Exposure to marketing, growth, or publisher-facing products
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WHY THIS ROLE IS DIFFERENT
You own the architecture. Not a feature factory. Not someone else's design doc. The technical execution of an AI product is yours to lead.
The agent is the product. You're not adding AI to an existing system. You're building and operating the system that is the AI. Every architectural decision
touches what Juliet can and can't do.
Hard problems, always. The system spans cloud sandboxes, streaming infrastructure, multi-step agent graphs, and a full-stack web product — for non-technical
users who can't course-correct a broken output. The bar is high.
Small team, real leverage. Your code ships to users the same week. No layers of approval.
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HOW TO APPLY
Send us:
1. A short note on the most complex agentic system you've shipped: what broke, and what you'd redo. A link to something you've built that involves agent graphs, tool use, or autonomous multi-step execution
2. What is one thing you would improve about Juliet? It could be a feature or a bug.

About Juliet AI, Inc.
About
www.juliet.space
Agentic AI Coding
Company social profiles
Similar jobs (10)
Most sales tools help you send emails. We’re building something different.
At Salesforge, we’re creating autonomous AI agents that can:
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And book meetings
All without human involvement.
Why this is interesting
A lot of AI products stop at “generate text.” We’re focused on outcomes.
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What you’ll be working on
You won’t be maintaining legacy systems.
You’ll be:
Designing and building core backend systems that power our AI agents
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About Orenda
Orenda is a fintech-enabled financial services company founded in 2017 and based in Ahmedabad, Gujarat. We work as a corporate DSA and channel partner for leading banks and NBFCs, helping individuals, professionals, and MSMEs access suitable financial solutions across business loans, personal loans, home loans, loan against property, and professional loans.
At Orenda, we combine financial expertise, technology, and streamlined processes to simplify the lending journey. We are building our own lending-tech platform to improve operational efficiency, strengthen lender and partner integrations, and develop technology-driven solutions that support our evolving business needs.
About the role
We're looking for a Lead Software Engineer who enjoys building as much as designing. You'll shape how our systems are architected, write a good share of the code yourself, and lead a team of 3 to 5 engineers, including AI/ML engineers.
This is a hands-on leadership role, not a pure management or architecture position. Your time will be roughly split like this:
Share of time
Leading the team ~30%
Solution design ~30%
Hands-on coding ~30%
Deployment and infrastructure~10%
What you'll work on
Solution design and architecture
• Turning business needs into technical designs that are practical to build and easy to maintain
• Making architecture decisions across services, integrations and data flows
• Estimating, scoping and planning new features with business and product stakeholders
• Shaping the solution design for AI/ML use cases alongside the AI/ML engineers
Engineering and delivery
• Writing production code in Python and Node.js
• Rolling out new features across our internal and partner-facing platforms, including our CRM and partner portal
• Continuously improving existing systems for performance, reliability and code quality
• Reviewing code and setting engineering standards for the team
Infrastructure and cloud
• Maintaining and upgrading our infrastructure, including a planned move to a major cloud platform
• Owning deployments and production stability together with the team
• Working with event-driven and messaging systems (NATS today, Kafka planned)
Team leadership
• Leading and mentoring a team of 3 to 5 engineers
• Planning and prioritising work, unblocking the team, and making sure things ship
• Building a culture of ownership, clear documentation and quality
What we're looking for
• 5 to 8 years of software engineering experience, with hands-on coding in your recent roles
• Strong command of Python and Node.js
• Proven experience designing and building backend systems and microservices that run in production
• Hands-on experience deploying and running workloads on at least one major cloud platform (AWS, Azure or GCP)
• Solid working knowledge of PostgreSQL
• Experience with messaging or event streaming systems such as NATS, Kafka or RabbitMQ
• Experience leading or mentoring a small engineering team
• Comfort estimating effort, breaking down features and planning delivery
• Enough understanding of AI/ML systems to guide their solution design and integration
• Clear communication with both technical and non-technical stakeholders
Good to have
• Experience working at a fintech, lending or financial services company
• Hands-on experience with Kafka
• Experience leading an infrastructure upgrade or cloud migration
• Experience building or scaling CRM or partner-facing portal products
Why Join Us?
- Build a growing lending-tech platform: Play a key role in shaping the technology behind a growing financial services business.
- Own technical decisions: Contribute directly to architecture, engineering standards, and technology direction.
- Stay hands-on: Combine solution design and technical leadership with meaningful coding responsibilities.
- Work with emerging technologies: Collaborate with AI/ML engineers and contribute to evolving platform capabilities.
- Lead and grow a team: Mentor engineers and help build a strong engineering culture as the technology function scales.
- Make a measurable impact: Build systems that improve operational efficiency and support business growth.

Role & Responsibilities
- Own end-to-end architecture, system design, development, and production deployment of scalable, AI-powered applications.
- Architect and develop high-performance backend services using Node.js, NestJS, TypeScript, Express.js, and Go.
- Design scalable web applications using React.js and Next.js, and cross-platform mobile applications using Flutter and Dart.
- Design distributed systems, microservices, event-driven architectures, and real-time applications capable of handling massive data volumes and high concurrent traffic.
- Design and optimize PostgreSQL/MySQL databases, MongoDB, Redis caching, database indexing, transactions, and query performance.
- Build real-time ride-booking, driver-allocation, location-tracking, and proximity-based matching systems using geospatial technologies such as PostGIS.
- Design and implement REST APIs, WebSockets, secure authentication, authorization, RBAC, and third-party integrations.
- Build and integrate Generative AI applications, LLM-powered chatbots, AI agents, RAG pipelines, embeddings, vector databases, tool calling, and intelligent automation workflows.
- Develop AI and backend services using Python and integrate LLM platforms such as OpenAI, Claude, and Gemini.
- Architect secure payment integrations, transaction workflows, webhook processing, idempotency, and payment reconciliation.
- Design and implement cloud-native infrastructure using AWS, Docker, CI/CD pipelines, and production monitoring tools.
- Ensure application security, scalability, reliability, performance, maintainability, and cost efficiency.
- Lead technical decision-making, code reviews, debugging, performance optimization, documentation, and mentoring of developers.
- Independently own critical engineering deliverables and drive products from concept and architecture through development, testing, deployment, and production support.
Preferred Candidate Profile
- 710+ years of software development experience, with substantial hands-on experience in technical architecture and production-grade application development.
- Expert-level proficiency in Node.js, NestJS, TypeScript, REST APIs, backend architecture, and microservices.
- Strong experience with React.js, Next.js, and modern frontend architecture.
- Hands-on experience with Flutter and Dart for Android and iOS application development.
- Proven experience designing scalable systems, handling large data volumes, concurrent workloads, and performance-critical applications.
- Strong experience with PostgreSQL, database design, indexing, query optimization, transactions, Redis, and geospatial systems.
- Practical experience building and deploying LLM-powered applications, AI agents, RAG systems, embeddings, vector search, and AI workflow automation.
- Proficiency in Python for AI integrations and backend services; Go language experience is highly desirable.
- Strong understanding of authentication, authorization, application security, payment integrations, and secure API design.
- Hands-on experience with AWS, Docker, CI/CD, Git, production deployments, logging, and monitoring.
- Familiarity with Kafka/RabbitMQ, Kubernetes, LangChain/LlamaIndex, and event-driven architectures is an advantage.
- Exceptional system-design, analytical, debugging, and problem-solving skills.
- Strong ownership, independent execution, technical leadership, communication, and mentoring abilities.
- Experience in startups or building products from scratch is highly desirable.
What We Expect
We are looking for a highly hands-on technical leader who can independently architect, design, develop, optimize, and deploy complex production systems. The ideal candidate must demonstrate genuine technical depth, strong engineering judgment, and the ability to lead end-to-end product development across backend, web, mobile, cloud, and AI technologies.
Proficient
Python Backend Development
Python, REST APIs, Microservices, FastAPI, Flask, Django, API Design, Authentication, Error Handling
Design, implement, and maintain scalable backend systems using Python frameworks. Build robust REST APIs, ensure secure authentication, and handle errors gracefully. Demonstrate expertise in microservices architecture and API design.
35
Proficient
React JS
React JS, Components, Hooks, State Management, API Integration, Responsive UI, Frontend Testing
Develop responsive and interactive user interfaces using React JS. Effectively use components, hooks, and state management. Integrate APIs and ensure frontend code is well-tested and maintainable.
30
Proficient
Gen AI / Agentic AI
LLMs, Agentic AI, LangChain, LangGraph, Google ADK, Semantic Kernel, Prompt Engineering, Tool Calling, RAG, Embeddings, Vector Search, Memory, Planning, Reasoning, Multi-Agent Systems, Guardrails, Azure OpenAI, Vertex AI, AWS Bedrock
Demonstrate hands-on experience with LLMs and agentic AI frameworks. Build, integrate, and optimize AI agents using modern tools and platforms. Show proficiency in prompt engineering, tool calling, RAG, embeddings, and multi-agent systems.
30
Advanced
Cloud & Deployment
AWS, Azure, GCP, Cloud Deployment, Containers, CI/CD, Application Hosting, Monitoring
Deploy applications to cloud platforms, manage containers, set up CI/CD pipelines, and monitor application health. Demonstrate familiarity with at least one major cloud provider.
Position Overview
We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and
maintain end-to-end software solutions spanning web platforms, desktop applications, and
autonomous AI agents capable of interacting with and controlling these software systems.
The ideal candidate will bridge traditional engineering software with cutting-edge artificial
intelligence to automate data processing and enhance operational decision-making. While
not strictly required, a background or strong interest in the energy sector—specifically
drilling and completion operations—is highly desirable.
Key Responsibilities
• Full Stack Development: Design, develop, and deploy robust web applications and
native desktop software utilized by engineering and operational teams.
• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-
driven workflows capable of interpreting data, executing commands, and safely
controlling desktop and web-based software.
• Workflow Automation: Translate complex workflows into intuitive software features
and autonomous agent actions, minimizing manual data entry and operational
bottlenecks.
• Data Integration: Handle high-frequency data streams and integrate them seamlessly
into user interfaces and backend AI models.
• Architecture & Scalability: Ensure high performance, security, and scalability across
cloud infrastructure (AWS/Azure), local desktop environments, and potential edge
computing setups.
• Cross-Functional Collaboration: Work closely with domain experts and end-users to
translate field challenges into technical product requirements.
Required Qualifications & Experience
• Experience: Minimum of 5 years of professional software development experience,
with a proven track record of delivering production-ready web and desktop
applications.
• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at
least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend
frameworks (React, Angular, or Vue.js), Node.js, and desktop application development
(Electron, WPF, Qt, or Tauri).
• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs
(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,
AutoGPT, or custom agent architectures.
• Automation & UI Control: Expertise in software control mechanisms using tools like
Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to
allow AI agents to navigate software.
• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud
platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.
Preferred Qualifications (Strong Plus)
• Industry Domain Expertise: Prior hands-on development experience within the oil and
gas sector, specifically focused on drilling, completions, rig operations, or subsurface
engineering software.
• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and
time-series databases.
• Experience deploying AI models and agents in edge or low-connectivity environments
(such as offshore rigs or remote drilling sites).
• Familiarity with safety-critical software design and cybersecurity standards in
industrial control systems (ICS/SCADA).
• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.
Strong Lead AI Engineer Profile with agentic systems architecture expertise
2
Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems
3
Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals
4
Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder
5
Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling
6
Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses
7
Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines
8
Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces
9
Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.
10
Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks
11
Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders
Strong Lead AI Engineer Profile with agentic systems architecture expertise
2
Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems
3
Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals
4
Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder
5
Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling
6
Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses
7
Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines
8
Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces
9
Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.
10
Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks
11
Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders
12
Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month

About the client
The client is building a suite of SaaS products for websites—products with clear product-market fit, strong customer pull, and the potential to become $100M+ businesses.
As they grow, they need engineers who go beyond feature delivery. They are looking for backend developers who want to build enduring systems, make practical decisions, and help us ship great products with high velocity.
What You’ll Do
- Work with product, design, and support teams to turn real customer problems into thoughtful, scalable solutions.
- Design and build robust backend systems, services, and APIs that prioritize long-term maintainability and performance.
- Use AI-assisted tooling (where appropriate) to explore solution trees, accelerate development, and reduce toil.
- Improve velocity across the team by building reusable tools, abstractions, and internal workflows—not just shipping isolated features.
- Dig into problems deeply—whether it's debugging a performance issue, streamlining a process, or questioning a product assumption.
- Document your decisions clearly and communicate trade-offs with both technical and non-technical stakeholders.
What Makes You a Strong Fit
- You’ve built and maintained real-world software systems, ideally at meaningful scale or complexity.
- You think in systems and second-order effects—not just in ticket-by-ticket outputs.
- You prefer well-reasoned defaults over overengineering.
- You take ownership—not just of code, but of the outcomes it enables.
- You work cleanly, write clear code, and make life easier for those who come after you.
- You’re curious about the why, not just the what—and you’re comfortable contributing to product discussions
Bonus if You Have Experience With
- Building tools or workflows that accelerate other developers.
- Working with AI coding tools and integrating them meaningfully into your workflow.
- Building for SaaS products, especially those with large user bases or self-serve motions.
- Working in small, fast-moving product teams with a high bar for ownership.
How’s the team?
- Open and flat hierarchy
- High-agency work with a get-stuff-done attitude
- Teams that focus on creating wins - for the org, the team and yourself - all fuelled by mentorship and empowerment
Our Culture
Some values we’ve lived by over these last 14 years:
We think like inventors.
>Invent the answer you wish existed. If it already exists, ask how it could exist better.<
We build for the love of it. And we build the best.
We don’t just copy and paste. We start from first principles—frame the problem, question the default, ship, improve, repeat—until it’s world-class.
Every version and experiment is a chance to push past our comfort zone and hone our craft. It isn’t easy—it takes patience and persistence—but it ends in work we’re proud of.
Ownership builds a rocket ship.
>It’s not the hours you put in your work that count; it’s the work you put in the hours.<
We’re here to build the business. When we see a problem, we own it end‑to‑end. We pull in the right people, ask for help early, track just enough to finish, and close the loop. We focus on what moves the needle, cut low‑impact work, and push hard when it counts—then recover.
That focus builds subject mastery. It helps get in the flow. It fuels passion and can spark healthy friction—and that’s all part of the game. We make a fuss when it matters, and once a call is made, we commit to it fully—whether we all agree or disagree.
Step up to stand tall.
>Greatness is a moving target.<
Chase excellence in your craft and take on bigger problems. Grow into a full-stack problem-solver and leader—whatever your domain. Improve with intent, work with people who push you, and never get too comfortable. That’s how we level up.
Benefits
- Relocation benefits - we’ll book your domestic travel if you are not in Bangalore and help you with 2 weeks of accommodation
- Homemade lunch at the office and a pantry with snacks, fresh coffee & tea
- All the IT essentials and tools you’ll need to be successful in your role, everyone at the office gets an external monitor, ergonomic seating and a mechanical keyboard
- Frequent outings, company-sponsored outdoor events, celebrations for milestones, trips for the entire team and sponsorships to participate at international company events at exotic destinations
- Profit-sharing bonuses based on company growth, tenure and performance
- Paid time off - maternity, paternity, and marriage leave
- Insurance for the whole family
About Juicelabs
Where creative engineering meets applied AI.
We build vertical, AI-native tools that unlock fresh insights and creative superpowers for clients in advertising, ecommerce, and beyond. We're a nimble team of founders and builders obsessed with using AI to solve real problems in ways that didn't exist eighteen months ago.
The Opportunity
A year ago, we would have posted this as a backend role. That role doesn't really exist any more.
Code has become nearly invisible. Agents write it, test it, and iterate on it faster than anyone could read it. What's left is the work above it: deciding what's worth building, designing systems that hold up at 10x, and building the setup that turns a clear spec into working software.
That's the job. At your level, it isn't one system. It's several workstreams, running at once.
You'll work directly with our Cofounder/CTO on products going from zero to one, with AI at the core of both what we build and how we build it. Real ownership, real scope, and an unusual amount of leverage: one engineer with good judgment and a well-tuned agent setup now ships what a small team used to.
What you'll do
- Own multiple workstreams in parallel. Two or three features of the same product moving at once, each with its own scope, edge cases, and failure modes. You decide where your attention goes this week, and nothing goes stale.
- Run a fleet, not a single agent. Design the setup that makes high-throughput work possible: how work gets broken down, specced, and run across many agents at once, so output scales without things breaking.
- Design the system. Service boundaries, data models, failure modes. Make the architectural calls before a line gets generated, and be able to explain the trade-off six months later.
- Write the spec. PRDs and technical designs are the new source code. A vague spec produces confidently wrong software, fast. Scope, edge cases, non-goals, what "done" means.
- Own it end to end. Ideation → design → build → deploy → monitor → iterate, including functional UX. Nobody hands you tickets.
- Set the workflow. Bring your harness: CLAUDE.md, AGENTS.md, subagents, custom commands, eval loops — whatever makes agents reliable rather than merely impressive. We want to steal your good ideas.
What we're looking for
- High agency. You see the gap and close it. You don't wait for direction, and you don't need to be chased for follow-through. This is the single trait we screen hardest for. And you can do it across several workstreams at once, without dropping threads.
- Real system design depth. You can reason about consistency, caching, queues, and scale — and about complexity, because you need to know when an elegant-looking solution is quietly quadratic. LeetCode ninja not required. Being able to explain why this won't blow up at 10x, very much required.
- Clear thinking, put to paper. You get the thinking straight first, then write it down so nobody has to guess: PRDs, design docs, PR comments. Writing is most of how you'll direct both humans and models, and muddy thinking on paper becomes muddy software.
- You've shipped to production. Deployed things, monitored them, been paged by them, fixed them. Docker, CI/CD, cloud infra. Our stack is mostly Python (FastAPI), Postgres, GCP/AWS — but we care more about how you think than which framework you've memorised.
- You orchestrate AI, not just use it. Not "I've tried Copilot," and not just "I use Claude Code." You've run multiple agents in parallel and developed opinions: how to split work so they don't step on each other, where they excel, where they confidently lie, how you structure a repo so they don't wander, and how you verify what comes back at volume.
- Startup energy. Multiple hats, fast cycles, and the judgment to balance "ship it now" against "will this survive contact with real users?"
Experience
3–6 years of professional experience (full-time positions, excluding internships).
Location / How to apply
On-site at our office in HSR Layout, Bangalore.
Apply through this posting, or email us with a link to the best thing you've built.
About PortOne
PortOne is building the reconciliation and data intelligence layer for payments across Korea and international markets. We are a Series B startup backed by Softbank and Hanwa Capital, powering multi-billion dollars in annualised settlement volume for 2,000+ merchants across Korea, Thailand, Singapore, Indonesia, and beyond.
We are building AI-native products for leading brands — intelligent automation layers on top of complex financial data pipelines. If you want to work at the intersection of fintech, data engineering, and applied AI, this is your role.
Culture and Values
* You will be joining a team that stands for making a difference.
* You will be joining a culture that identifies more with Sports Teams rather than a 9 to 5 workplace.
* Your will have peers who are/have
** Highly Self Driven with A sense of purpose
** High Energy Levels - Building stuff is your sport
** Ownership - Solve customer problems end to end - Customer is your Boss
** Hunger to learn - Highly motivated to keep developing new tech skill sets
Your Work Ethic
* You are an athlete and building apps is your sport.
* Your passion drives you to learn and build stuff and not because your manager tells you to.
* You obsess over correctness — a bug in a settlement figure or a silent data drop is not acceptable to you.
* You have an eye for detail that most engineers skip past, and you take pride in getting it exactly right.
* Your work ethic is that of an athlete preparing for your next marathon. Your sport drives you and you like being in the zone.
* You are NOT a clockwatcher renting out your time, and NOT have an attitude of "I will do only what is asked for"
What will you do?
- Build and maintain financial data ingestion pipelines that pull settlement and transaction data from marketplace platforms (Amazon, Shopee, TikTok, Qoo10, Rakuten) on behalf of large brands operating across multiple Asian markets.
- Own reconciliation workflows end-to-end — from raw marketplace data to verified, merchant-ready settlement reports — ensuring every figure is correct and every discrepancy is surfaced, not swallowed.
- Design and implement AI-native features that automate financial analysis: agentic triage of settlement mismatches, root-cause detection across large transaction volumes, and intelligent alerting for ops and merchant teams.
- Instrument data quality and health monitoring so that silent failures — missing records, schema shifts, delayed ingestion — are caught before they reach the merchant.
- Build APIs and tooling that enable PortOne's ops and merchant success teams to investigate, verify, and close financial discrepancies faster and with more confidence.
- Expand platform coverage by integrating new marketplaces and new report types, working closely with data formats that are often inconsistent, undocumented, or changing without notice.
- Uphold rigorous engineering standards — correctness in financial data is not negotiable, and you treat edge cases and off-by-one errors with the same seriousness as a production incident.
- Uphold high engineering standards across codebases and processes.
- Collaborate with product, design, infrastructure, and operations stakeholders.
Skills and Experience
* Have ideally 4 to 6 Years of experience shipping high quality products/live features and workflows
*AI-native development — you build products where AI is a first-class component, not a bolt-on.
* Strong backend engineering foundation — Go (Preferred), Python, or equivalent; REST/gRPC APIs; database design.
* Understands how to build scalable, resilient, and observable distributed systems.
* Must have built data flows and applications end to end taking full ownership
Preferred Skills and Background
*Prior experience/built apps in golang backend
*Data and data engineering background — comfortable with data pipelines, ETL/ELT patterns, event-driven architectures, reconciliation logic, or analytical workloads.
*AI agentic development — experience building or working with agent frameworks, tool-use patterns, LLM orchestration, or automated reasoning pipelines.










