Principal Engineer at Recruiting Bond Ā· Bengaluru (Bangalore), Mumbai Ā· 10 - 16 years Ā· ā¹75L - ā¹130L / yr Ā· Bootstrapped Ā· Posted 22 May 2026

šØ Weāre Building a āTop 1% Engineering Orgā
Weāre building a high-talent-density, AI-first R&D organization from scratch ā inside a publicly listed company undergoing a full-scale transformation.
Think:
ā Rewriting legacy systems into AI-native architectures
ā Embedding LLMs + Agentic AI into core workflows
ā Reimagining platforms, infra, and data systems for the next decade
This is the kind of shift youād expect from Google, Microsoft, or Meta ā
Except you get to build it from day 0 ā scale it globally.
About the Role / Team
We are building a next-generation AI-first R&D organization in Bengaluru, focused on solving complex problems across LLMs, Agentic AI systems, distributed computing, and enterprise-scale architectures.
This initiative is part of a publicly listed global company investing heavily in AI-driven transformation, re-architecting its platforms into intelligent, autonomous systems powered by large language models, workflows, and decision engines.
You will be working on:
- Agentic AI systems & LLM-powered workflows
- Distributed, scalable backend systems
- Enterprise-grade AI platforms
- Automation-first engineering environments
š The Mandate
Own and evolve the technical backbone of an AI-first enterprise platform.
You will define architecture across LLM-powered systems, distributed services, and data platforms ā and lead critical transformations from legacy ā AI-native systems.
š§© What Youāll Do
- Architect large-scale distributed systems powering AI-driven workflows
- Lead 0ā1 and 1āN platform builds (LLM integrations, agentic systems, orchestration layers)
- Redesign legacy systems into scalable, modular, AI-native architectures
- Drive system design excellence across teams (APIs, infra, observability, reliability)
- Make high-stakes decisions on trade-offs (latency, cost, scalability, model performance)
- Mentor senior engineers and influence engineering culture/org standards
- Partner with product, data, and leadership on long-term technical strategy
š§ What Weāre Looking For
- Proven track record building high-scale backend or platform systems
- Deep expertise in distributed systems, microservices, cloud (AWS/GCP/Azure)
- Strong exposure to data systems/infra / Data / real-time architectures
- Experience or strong interest in LLMs, GenAI, or AI system design
- Exceptional system design, abstraction, and problem-solving ability
- High ownership mindset ā you think in terms of systems, not tickets
- Strong coding skills in Python / Java / Go / Node.js
- Solid understanding of data structures, system design basics, and backend architecture
- Experience building scalable APIs and services
- Familiarity or curiosity around AI/LLMs, async systems, or event-driven design
- Strong debugging, problem-solving, and ownership mindset
- Solve hard system problems (latency, scale, reliability)
- Drive cross-team technical decisions and standards
- Mentor senior engineers and influence org-wide architectureĀ
- Design large-scale distributed systems and backend platforms
- Mentorship & Technical LeadershipĀ
- Expertise in system design, scalability, and performance optimization
Nice to Have
- Experience integrating LLMs, vector databases, or AI pipelines
- Contributions to architecture at scale
- Experience with Agentic AI / LLM orchestration frameworks
- Background in product engineering or platform companies
- Exposure to global-scale systems (millions of users / high throughput)
š„ What Sets You Apart
- Built platforms used by millions of users / high-throughput systems
- Experience with event-driven systems, stream processing, or infra platforms
- Prior work on AI/ML platforms, model serving, or intelligent systems

About Recruiting Bond
About
Recruiting Bond is a global leader in Recruitment Process Outsourcing (RPO), Executive Search, Headhunting, Talent Mapping, and Workforce Consulting. Founded by Pavan B, we are on a mission to power businesses through transformative talent strategies that scale teams, accelerate innovation, and unlock human potential.
With a presence across 25+ industriesāfrom IT, Healthcare, and FinTech to Gaming, BioTech, and Web3āwe specialize in hiring that drives outcomes. Our domain expertise spans high-growth startups to Fortune 500 companies, delivering elite CXO and leadership talent, strategic workforce solutions, and inclusive hiring at scale.
We help businesses:
āļø Hire the right leaders and builders
āļø Scale globally with speed and precision
āļø Build talent-first roadmaps from MVP to IPO
Whether you're launching, scaling, or transformingāRecruiting Bond is your strategic partner in talent.
š¹ Industries: Technology | Healthcare | FinTech | Retail | Manufacturing | EdTech | Crypto | Real Estate | Web3 | Logistics | Energy & more
š¹ Services: Executive Hiring | RPO | Talent Strategy | Workforce Design | Startup Consulting | Diversity Recruitment
šØ Letās build the futureātogether: https://recruitingbond.c
Tech stack
Candid answers by the company
We help businesses:
āļø Hire the right leaders and builders
āļø Scale globally with speed and precision
āļø Build talent-first roadmaps from MVP to IPO
Whether you're launching, scaling, or transformingāRecruiting Bond is your strategic partner in talent.
Similar jobs (10)
Most sales tools help you send emails. Weāre building something different.
At Salesforge, weāre creating autonomous AI agents that can:
Find the right prospects
Generate highly personalized outreach
Run conversations
And book meetings
All without human involvement.
Why this is interesting
A lot of AI products stop at āgenerate text.ā Weāre focused on outcomes.
That means solving problems like:
How do you generate messages that actually get replies?
How do you evaluate and improve agent performance over time?
How do you orchestrate millions of AI-driven interactions reliably?
How do you combine structured data + LLMs in a way that scales?
If you enjoy working at the intersection of systems + AI + real-world feedback loops, this will feel like a playground.
What youāll be working on
You wonāt be maintaining legacy systems.
Youāll be:
Designing and building core backend systems that power our AI agents
Creating APIs and services that handle high-scale, real-time workflows
Working with queues (Kafka / SQS / RabbitMQ) to orchestrate async systems
Thinking deeply about performance, cost, and reliability in AI pipelines
Shipping features end-to-end with a small, senior team
The team
Weāre a small group of experienced builders. We move quickly, care about quality, and avoid unnecessary process.
No layers of management.
No long planning cycles.
Lots of ownership and autonomy.
What weāre looking for
5+ years of backend engineering experience
Strong system design fundamentals
Experience with distributed systems and async processing
Familiarity with relational and/or document databases
Clear communicator, low ego, high ownership
Why join
Youāll work on a product where the output is measurable (meetings booked, revenue generated)
Youāll have real ownership from day one
Youāll be early in building a new category (AI sales agents)
Youāll grow as fast as we do
Technical Architect ā Product Engineering
Experience: 15+ Years
Location: Pune, India
Employment Type: Full-time
Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design
About the Role
We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.
The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.
Key Responsibilities
- Own the overall product architecture and technical roadmap.
- Design and build scalable, secure, and highly available enterprise applications.
- Lead the design and implementation of new product features from concept to production.
- Remain hands-on with coding and contribute to critical product components.
- Drive architecture reviews, code quality, performance optimization, and engineering best practices.
- Lead cloud architecture, security, scalability, and DevOps initiatives.
- Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
- Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.
Required Skills & Qualifications
- 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
- Strong hands-on expertise in Python and modern backend frameworks.
- Deep experience with AWS services and cloud-native application architecture.
- Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
- Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
- Strong knowledge of SQL and NoSQL databases.
- Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
- Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
- Strong analytical, problem-solving, and decision-making skills.
Senior Software Engineer ā Backend
Company: House of EdTech (Goenka Kachave LLP)
Location: Bangalore, Hybrid
Job Type: Full-Time
Experience: 5+ Years
About the Role
House of EdTech is looking for a Senior Software Engineer ā Backend to design, develop, and scale high-performance backend services and APIs supporting products used by millions of learners.
Youāll work closely with Product, Frontend, Data, and Engineering teams while taking end-to-end ownership of backend features and contributing to system architecture and technical decisions.
What You'll Do
- Design and develop scalable backend services and REST APIs.
- Build reliable systems capable of handling high traffic and large data volumes.
- Own backend features from design and development through deployment and monitoring.
- Work with microservices, databases, and distributed systems.
- Identify and solve performance, scalability, reliability, and security challenges.
- Participate in system design and architecture discussions.
- Conduct code reviews and contribute to engineering best practices.
- Mentor junior and mid-level engineers.
- Monitor production systems and troubleshoot incidents.
What We're Looking For
- 5+ years of professional backend development experience.
- Strong hands-on experience with Java, Python, Scala, C++, or a similar language.
- Experience building and operating large-scale distributed systems.
- Strong understanding of REST APIs, microservices, and databases.
- Experience with cloud/infrastructure technologies such as GCP, Docker, or Kubernetes.
- Strong software engineering fundamentals, including security, reliability, testing, and code quality.
- Experience with system design, architecture, and technical decision-making.
- Strong communication and cross-functional collaboration skills.
- Experience mentoring engineers is a plus.
Why Join House of EdTech?
- Work on products impacting millions of learners.
- Solve challenging backend and scalability problems.
- Take significant ownership of architecture and engineering decisions.
- Opportunity to grow into technical leadership and architectural ownership.
- Work in a fast-growing technology environment.
Strong Tech Lead / Staff Engineer / Lead Engineer Profiles
2
Mandatory (Experience 1) - Must have minimum 6+ years of overall Software Engineering/Development experience building production backend systems.
3
Mandatory (Experience 2) - Must have Tech Lead ownership, with experience setting technical direction, architecture, frameworks, or engineering standards used by other engineers.
4
Mandatory (Experience 3) - Must have strong hands-on Backend development experience with deep proficiency in at least one backend programming language. (Python, Java, Golang etc)
5
Mandatory (Experience 4) - Must have strong System design/distributed systems experience, including architectural trade-offs, scalability, failure modes, reliability, and long-term maintainability.
6
Mandatory (Experience 5) - Must have strong CS fundamentals in Data Structures & Algorithms, Operating Systems, and Networking, with the ability to apply them to complex backend/system problems
7
Mandatory (Experience 6) - Must have owned complex, ambiguous, or business-critical engineering problems end-to-end, demonstrating clear technical judgment, trade-offs, problem-solving, and measurable technical/business impact; not limited to feature implementation.
8
Mandatory (Experience 7) - Must have formal technical leadership experience, including mentoring Senior Engineers, conducting design/code reviews, driving engineering quality, and leading technical decisions across a team.
9
Mandatory (Experience 8) - Must be a hands-on IC + Tech Lead, with approximately 70ā80% hands-on coding/engineering involvement, not a pure people-management profile.
10
Mandatory (Company) - Product Companies / Startups / B2B SaaS
11
Mandatory (Education) - CS degree or equivalent (B.Tech/B.E./B.S.)
12
Preferred (Skills) - Experience with Kafka/NATS/RabbitMQ, AWS, Docker/Kubernetes, CI/CD, observability, security/compliance, multi-tenant systems, and financial/billing platforms.
About the Role
We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.
This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.
This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions ā not people management or process.
Responsibilities
- Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
- Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
- Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
- Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
- Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
- Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
- Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
- Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.
Qualifications
- Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
- Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
- Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
- Advanced knowledge of Kubernetes and Terraform in production environments.
- Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
- Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
- Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
- Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
- Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
- Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
- Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
- Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.
Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.
Our Culture
Who we are:
Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.
How we work:
- We move Blitzy Fast: Time is both our companyās and our clientsā most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
- Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
- Passion for Invention: Weāre pushing the frontier of whatās possible, requiring constant innovation and iteration.
- We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
- We believe in being āeveryday athletesā: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities forĀ
Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.
Strong Python Developer profile with robust AWS exposure
2
Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS
3
Mandatory (Tech skill 1): Must have strong working knowledge of Python.
4
Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR
5
Mandatory (Tech skill 3): Must be able to write and understand REST APIs
6
Mandatory (Tech skill 4): Experience designing and architecting scalable backend applications/services on AWS, including making decisions around application architecture, APIs, databases, and AWS services
7
Mandatory (Tech skill 5): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab
8
Mandatory (Tech skill 6): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB
9
Mandatory (Tech skill 7): Must have familiarity with Linux commands and shell scripting
10
Mandatory (Skill 1): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance
11
Mandatory (Skill 2): Must have strong communication skills
12
Preferred (Tech skill 2): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools
13
Preferred (Tech skill 3): Basic understanding of CI/CD pipelines
14
Preferred (Tech skill 4): Experience with Docker or container-based applications
15
Preferred (Tech skill 5): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation
Senior Backend Engineer
Node.js, System Design & Production Platforms
š Mumbai (On-site) | Full-time | 5+ years
About the Role:
Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.
We are hiring a Senior Backend Engineer to own the backend architecture of a complex production AI platform on a dedicated client engagement: API design and data modelling, multi-tenancy, orchestration of long-running agent workloads, and the services that manage user projects and generated output.
We are open to full stack engineers whose primary strength and interest is backend. If you have shipped full stack work but the backend is where you do your deepest engineering, you are a fit for this role.
The mandatory requirement for this role is hands-on production experience as a senior backend engineer building complex, scalable systems in Node.js, with end-to-end ownership of architecture, data, and operations on at least one live platform.
The role is hands-on and architectural.
Expect to design system architecture, lead a small group of backend engineers, build the hardest parts yourself, set engineering standards, and partner closely with frontend, AI, and DevOps engineers.
A typical week includes an architecture decision on a new service, hands-on implementation of a critical path, a code review with mid-level engineers, and a working session with the AI engineer on an integration contract.
Responsibilities:
System Architecture
Own the backend architecture across engagements.
Make and document decisions on service boundaries, data models, API contracts, deployment topology, and trade-offs.
Hands-on Backend Delivery
Lead by example on complex modules, performance-critical paths, and high-risk areas using Node.js (Express, NestJS, Fastify) with TypeScript.
Pick up Python (FastAPI) where engagements require it.
Database Design and Performance
Drive PostgreSQL schema design, indexing, query optimisation, migrations, and capacity planning.
Set the data-modelling standard across the pod.
Caching, Queues, and Workflows
Design caching (Redis), event-driven patterns (Kafka, RabbitMQ, SQS, NATS), and long-running workflow orchestration (Temporal, BullMQ, Celery, or equivalent).
Handle retries, idempotency, and failure recovery.
Multi-Tenancy and Platform Patterns
Design and implement multi-tenant data isolation, RBAC, audit logging, and resource quotas appropriate to enterprise-grade products.
API and Integration Design
Set the standard for REST, GraphQL, and gRPC contracts.
Drive versioning, authentication (OAuth, JWT, SSO), security by default, and developer ergonomics.
Observability and Operations
Instrument services with OpenTelemetry, Prometheus, and Grafana.
Define SLOs, lead incident response, and write postmortems.
Code Quality and Mentorship
Run code reviews, define conventions, mentor mid-level engineers, and raise the engineering bar.
AI-Assisted Engineering Discipline
Use Claude, Cursor, and similar tools day to day.
Set the team standard for prompts, patterns, AI-assisted review, and validation of AI-generated backend code.
Client Engagement
Represent Unico Connect in technical conversations with customers.
Defend architectural decisions, communicate trade-offs, and manage scope.
Requirements:
Hands-on Production Experience as a Senior or Lead Backend Engineer in Node.js (Mandatory)
Must have personally built and shipped complex production systems in Node.js, owning architecture, data, and operations on at least one live engagement.
Full stack engineers whose deepest work is on the backend qualify.
POCs and internal tools alone do not qualify.
5+ Years of Professional Backend Engineering Experience
With at least 1 to 2 years in a senior or lead role with direct responsibility for technical decisions and team output.
Deep Node.js and TypeScript Proficiency
Strong with Express, NestJS, or Fastify.
Comfort with async patterns, streams, worker threads, and performance profiling.
Python as a Strong Plus
Hands-on production experience with FastAPI, Django, or Flask is a meaningful advantage.
Willingness and demonstrated ability to pick up Python as engagements demand is required.
PostgreSQL Depth
Schema design, normalisation, indexing, query performance, migrations, and at least one production system where you owned the data model end to end.
Caching and Event-Driven Architecture
Hands-on with Redis (or equivalent) and message queues or event-driven patterns (RabbitMQ, SQS, Kafka, NATS).
AWS Depth
Hands-on production experience with EC2, S3, RDS, IAM, VPC, ECR, and at least one of EKS, ECS, or Lambda.
Comfort owning deployment, monitoring, and cost.
System Design and End-to-End Ownership
Able to take an ambiguous problem, break it into components, evaluate alternatives, produce an architecture that holds up under review and load, plan execution, and ship with limited supervision.
AI-Assisted Engineering Experience
Daily use of Claude, Cursor, Copilot, or equivalent.
Strong discipline for reviewing and validating AI-generated backend code.
Excellent Written and Spoken English
Experience working directly with international clients.
Confident defending architectural choices in writing and in review.
Nice to Have:
- Workflow orchestration (Temporal, Airflow)
- GraphQL (Apollo, gRPC)
- Sandboxed execution environments
- Multi-tenant SaaS experience
- OpenTelemetry instrumentation
- Prior agency or consulting experience
Key Responsibilities
ā Lead the architecture, design, development, and delivery of scalable backend services
using Python.
ā Own technical direction and architectural decisions for backend systems and services.
ā Design and build robust RESTful APIs, microservices, and distributed systems
capable of handling high-scale workloads.
ā Design and implement real-time communication systems, including WebSocket-based
services, where required.
ā Drive system performance, scalability, reliability, availability, and security.
ā Lead performance optimization, capacity planning, monitoring, debugging, and
production issue resolution.
ā Establish and promote best practices around code quality, testing, observability, CI/CD,
and production readiness.
ā Collaborate closely with frontend, product, DevOps, infrastructure, and other
cross-functional teams to deliver end-to-end solutions.
ā Mentor and provide technical guidance to engineers, contributing to overall team growth
and engineering excellence.
ā Review code and architecture designs, identify technical risks, and drive improvements
across backend systems.
ā Take ownership of complex technical problems and deliver reliable, maintainable,
production-grade solutions.
Required Skills & Qualifications
ā 5+ years of software engineering experience, with significant experience in backend
development.
ā Strong expertise in Python and experience building production-grade backend
applications.
ā Proven experience designing and developing REST APIs and microservices
architectures.
ā Strong understanding of distributed systems, scalability, fault tolerance, and
high-availability architectures.
ā Hands-on experience with WebSockets and real-time backend integrations.
ā Strong experience with SQL/NoSQL databases, caching systems, and data-intensive
applications.
ā Experience with performance optimization, monitoring, logging, debugging, and
production operations.
ā Strong understanding of software engineering principles, design patterns, and clean
architecture.
ā Proven ability to lead technical initiatives and make sound architectural decisions.
ā Strong communication, collaboration, and technical leadership skills.
ā Experience mentoring engineers and conducting effective code and design reviews.
About the Role
We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership ā from backend AI architecture to frontend user experiences ā and can align engineering decisions with measurable product outcomes.
You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.
Example Project
Design and deploy a multi-agent AI system to automate critical stages of a companyās sales cycle, including:
- Generating client proposals using historical SharePoint data and CRM insights
- Summarizing meeting transcripts
- Drafting follow-up communications
- Feeding structured insights into dashboards and workflow tools
The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.
Key Responsibilities
- Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
- Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
- Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
- Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
- Drive architecture decisions balancing scalability, performance, and security
- Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
- Mentor junior engineers and evolve into a broader leadership role as the team grows
Ideal Candidate Profile
Experience Requirements
- 5+ years in full-stack development (Python backend + React/JavaScript frontend)
- Strong experience in API and microservice integration
- 2+ years leading technical teams and coordinating distributed engineering efforts
- 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
- Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions
Technical Expertise
- Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
- Ensuring backend and AI systems are scalable, reliable, observable, and secure
- Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
- Experience building production-grade AI systems within enterprise SaaS ecosystems
Experience: 8+ years, senior candidates only | Type: Full-time | Location: Remote (India)
Ā ---
Ā WHAT WE'RE BUILDING
Ā See http://www.juliet.space
Ā We're building Juliet, an AI that runs marketing end to end. Our users are marketers, founders, CEOs, growth leads, agencies, and SMBs ā not developers. They
Ā tell Juliet the goal. She plans, writes production code, and ships real marketing: conversion-optimized websites, launch assets, campaigns, audits, autonomously.
Ā 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 ā plan, build, self-correct,
Ā recover, ship.
Ā 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
Ā modules. The agent isn't bolted onto the product. She is the product.
Ā Small team, big ambitions. You'll ship things users touch daily, not write tickets about them.
Ā ---
Ā THE ROLE
Ā 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
Ā streaming pipeline, the state and memory systems ā and setting technical direction for the engineers working alongside you.
Ā 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
Ā between.
Ā 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
Ā features when needed.
Ā ---
Ā THE STACK
Ā AI agent (primary): Python 3.11, LangGraph 1.x + LangChain, Anthropic / Google / OpenAI model providers
Ā API (primary): NestJS 11, Supabase, Redis, PostgreSQL, Server-Sent Events
Ā Infra (primary): Modal cloud sandboxes, Docker, Netlify deployments
Ā Frontend (secondary): Next.js 15, React 19, TypeScript, Zustand, CodeMirror 6, XTerm.js
Ā Monorepo: Turborepo, pnpm
Ā ---
Ā WHAT YOU'LL WORK ON
Ā The majority of your time is here:
Ā Agentic AI workflows ā Design, extend, and harden the LangGraph agent graph: multi-step planning, code generation, tool dispatch, self-correction, and recovery
Ā across 83 tools and 63 skill modules. This is the core of the product.
Ā Real-time streaming architecture ā The SSE pipeline that carries every agent action from the Python backend through NestJS to the browser: event framing,
Ā reconnection, health monitoring, interrupt handling for plan approvals and clarifying questions.
Ā Agent execution environments ā Sandbox lifecycle on Modal: container spin-up, file sync, terminal I/O, command execution, and live preview with per-asset esbuild
Ā bundling. The agent lives here.
Ā State and memory systems ā LangGraph Postgres checkpointers, middleware-injected context (goals, design docs, memory anchors), conversation summarization. How
Ā the agent knows what it knows.
Ā Backend API and data layer ā NestJS services, Supabase schema, Redis caching, quota enforcement, webhook handling. The plumbing the agent depends on.
Ā Marketing intelligence pipelines ā AEO, CRO, and brand-perception audit engines: multi-LLM probing, parallel inference, streamed structured reports, result
Ā caching. Audit-at-scale infrastructure.
Ā The remaining ~25% of your time:
Ā Full-stack product features ā Collaboration (roles and permissions), the Netlify deployment pipeline, subscription and quota flows, onboarding. You'll ship these
Ā end to end ā backend first, frontend to close the loop.
Ā ---
Ā WHAT WE'RE LOOKING FOR
Ā Must-have:
Ā - 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
Ā the norm for people who thrive here.
Ā - Both worlds on your resume: engineering rigor inside a large company and 0-to-1 ownership at an early-stage startup.
Ā - Production agentic systems experience. You've built and operated LLM agent systems in production with LangGraph, LangChain, or equivalent ā agent graphs, tool
Ā use, state management, prompt engineering, evals. This means well beyond calling a chat endpoint.
Ā - Strong Python. You design and ship production Python daily. The agent codebase is yours to own.
Ā - Architect-level system design. You can own how data flows across four services, make tradeoffs under uncertainty, and defend every call.
Ā - AI-native development workflow. You drive Claude Code, Codex, or similar agentic tools as everyday instruments ā not occasionally. You have opinions about
Ā working with coding agents because you do it constantly.
Ā - Real-time backend systems. You've built SSE, WebSocket, or streaming API infrastructure in production ā not just consumed it.
Ā - Strong TypeScript. The API layer and most product features are in TypeScript. You're productive in it.
Ā Strong plus:
Ā - Background in developer tools, IDEs, or coding/execution platforms
Ā - Container runtimes and sandboxed execution (Modal, E2B, Firecracker, or similar)
Ā - Depth in PostgreSQL, Redis, and Supabase
Ā - LLM observability and evals tooling (LangSmith or similar)
Ā - NestJS or equivalent Node.js API framework experience
Ā - React/Next.js ā enough to ship a full-stack feature without handoff
Ā - Exposure to marketing, growth, or publisher-facing products
Ā ---
Ā WHY THIS ROLE IS DIFFERENT
Ā Ā
Ā 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.
Ā 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
Ā touches what Juliet can and can't do.
Ā Hard problems, always. The system spans cloud sandboxes, streaming infrastructure, multi-step agent graphs, and a full-stack web product ā for non-technical
Ā users who can't course-correct a broken output. The bar is high.
Ā Small team, real leverage. Your code ships to users the same week. No layers of approval.
Ā ---
Ā HOW TO APPLY
Ā Send us:
Ā 1. A short note on the most complex agentic system you've shipped: what broke, and what you'd redo.Ā A link to something you've built that involves agent graphs, tool use, or autonomous multi-step execution
Ā 2.Ā What is one thing you would improve about Juliet? It could be a feature or a bug.






