Backend Python Engineer - Business Embedded Role

Job Title: Platform Engineer

Location: Bangalore(Onsite)

Experience Level: 3-8

Salary Range: 20-30LPA

Description:

Join a team building an AI-native enterprise platform that helps businesses make faster, smarter and more consistent operational decisions using AI, enterprise data and workflow automation.

Design and build the core platform for enterprise decision workflows. Develop reusable workflow and decision runtimes. Build scalable, cloud-native distributed systems and event-driven architectures. Design enterprise-grade APIs and platform services. Build integrations with systems such as SAP and Oracle. Develop secure multi-tenant services with authentication and RBAC. Build and manage AWS cloud infrastructure and deployment systems. Implement monitoring and observability for production systems. Support both cloud and on-premise deployments. Enable faster onboarding and deployment of new enterprise workflows.

Requirements:

- Strong hands-on experience with Python

- FastAPI

- PostgreSQL

- Docker

- AWS

- Practical experience with Redis

- Kafka/event streaming

- REST APIs

- CI/CD

- Git

- Good understanding of Kubernetes

- Distributed systems

- Event-driven architecture

- Enterprise SaaS

- Microservices

- Strong backend engineering fundamentals

- Ability to design scalable, reliable and production-ready systems

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.

We are looking for a hands-on Engineering Lead who can own backend engineering, DevOps, and delivery management.

This is not a coordination-only role. You will contribute technically while establishing the processes, accountability, and

operating rhythm needed for predictable delivery. You will manage multiple engineers and effectively use AI coding

agents and automation tools to improve the team's output without compromising quality.

Key Responsibilities

• Own the architecture, development, deployment, and reliability of our backend systems.

• Lead engineers through clear goals, task breakdowns, ownership, reviews, and regular feedback.

• Establish a process-oriented delivery system covering planning, estimation, execution, testing, release, and

retrospectives.

• Translate product requirements into technical plans, milestones, dependencies, and measurable deliverables.

• Track execution proactively, identify delivery risks early, and communicate status clearly.

• Remain hands-on with critical development, debugging, architecture, code reviews, and production issues.

• Own CI/CD, infrastructure, observability, deployment practices, and operational readiness.

• Improve engineering quality through coding standards, automated testing, documentation, and review processes.

• Delegate work effectively across team members according to their strengths and development needs.

• Use AI coding agents and engineering automation to parallelise suitable work, while reviewing and validating all

outputs.

• Build a culture of accountability in which work has clear owners, acceptance criteria, deadlines, and definitions of

done.

• Collaborate closely with product and business stakeholders to balance speed, scope, quality, and technical debt.

What We Are Looking For

• 6+ years of backend engineering experience.

• At least 2 years of experience leading or managing an engineering team.

• Strong hands-on backend development experience with Python, FastAPI, Django + Django REST Framework, and

PostgreSQL.

• Practical experience with cloud infrastructure (AWS), DevOps, CI/CD, containers (Docker), monitoring, and

production operations.

• Experience working in a mature, process-oriented engineering environment.

• Demonstrated ability to improve delivery predictability and engineering throughput.

• Strong understanding of agile planning, estimation, sprint execution, incident management, and retrospectives.

• Ability to manage multiple people and concurrent streams of work.

• Experience reviewing architecture, pull requests, test plans, and production-readiness requirements.

• Strong written and verbal communication skills.

• Ability to give direct, constructive feedback and hold team members accountable.

• Sound judgement about when to build, delegate, automate, or reduce scope.

Tech Stack

Must-have: Python, FastAPI, Django + Django REST Framework, PostgreSQL, SQLAlchemy (async) + asyncpg, Pydantic,

REST API design + JWT authentication, Docker, AWS (ECS, ALB, ECR, CloudWatch, S3, Secrets Manager), Git.

Strongly preferred: Redis, Elasticsearch / OpenSearch, WebSockets, Payment gateways (Razorpay / Cashfree), Third-

party / ERP integrations, CI/CD (AWS CodeBuild or GitHub Actions).

Nice-to-have: Frappe / ERPNext + MariaDB, Microservices architecture, PostHog / CleverTap / Firebase, B2B e-commerce

or order management experience.

AI-Assisted Engineering

The ideal candidate should be comfortable incorporating AI into the software-development lifecycle. This includes:

• Breaking work into tasks that can be delegated safely to coding agents.

• Running multiple human and agent-led workstreams concurrently.

• Providing agents with clear context, constraints, and acceptance criteria.

• Reviewing generated code for correctness, security, maintainability, and architectural fit.

• Using automation to accelerate testing, documentation, refactoring, and operational workflows.

• Measuring whether AI tooling produces genuine delivery improvements.

We do not expect blind reliance on generated output. The Engineering Lead remains accountable for the quality and

correctness of everything shipped by the team.

Success in the First 90 Days

• Understand the existing architecture, infrastructure, team capabilities, and delivery bottlenecks.

• Take ownership of backend and DevOps execution.

• Introduce a consistent planning, tracking, review, and release cadence.

• Establish visibility into ownership, progress, dependencies, and delivery risks.

• Improve CI/CD, testing, monitoring, and production-readiness practices.

• Create an effective delegation model across engineers and AI agents.

• Deliver at least one meaningful product or platform milestone predictably from planning through production.

Nice to Have

• Experience scaling an early-stage or growing engineering team.

• Experience hiring, mentoring, and performance-managing engineers.

• Experience with infrastructure as code, security practices, and cloud-cost optimisation.

• Experience managing migrations, reliability improvements, or legacy-system modernisation.

• Previous experience introducing AI-assisted development workflows into an engineering team.

Who Will Succeed in This Role

You are likely to succeed if you are equally comfortable discussing architecture, reviewing code, resolving a production incident, planning a release, and having an accountability conversation with an engineer. You bring structure without creating unnecessary bureaucracy and know how to turn product priorities into consistent, high-quality delivery.

Role Overview:

We are seeking a backend-focused Software Engineer with deep expertise in REST APIs,

real-time integrations, and cloud-based application services. The ideal candidate will build

scalable backend systems, integrate real-time data flows, and contribute to system design

and documentation. This is a hands-on role working with global teams in a fast-paced, Agile

environment.

Key Responsibilities:

• Design, develop, and maintain REST APIs and backend services using Python, FastAPI,

and SQLAlchemy.

• Build and support real-time integrations using AWS Lambda, API Gateway, and

EventBridge.

• Develop and maintain Operational Data Stores (ODS) for real-time data access.

• Write performant SQL queries and work with dimensional data models in PostgreSQL.

• Contribute to cloud-based application logic and data orchestration.

• Containerize services using Docker and deploy via CI/CD pipelines.

• Implement automated testing using pytest, pydantic, and related tools.

• Collaborate with cross-functional Agile teams using tools like Jira.

• Document technical workflows, APIs, and system integrations with clarity and

consistency.

• Should have experience in team management

Required Skills & Experience:

• 8+ years of backend or integrations engineering experience.

• Expert-level knowledge of REST API development and real-time system design.

• Strong experience with: Python (FastAPI preferred), SQLAlchemy.

• PostgreSQL and advanced SQL.

• AWS Lambda, API Gateway, EventBridge.

• Operational Data Stores (ODS) and distributed system integration.

• Experience with Docker, Git, CI/CD tools, and automated testing frameworks.

• Experience working in Agile environments and collaborating with cross-functional

teams.

• Comfortable producing and maintaining clear technical documentation.

• Working knowledge of React is acceptable but not a focus.

• Hands-on experience working with Databricks or similar data platforms.

Education & Certifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field (required).

• Master’s degree is a plus.

• Certifications in AWS (e.g., Developer Associate, Solutions Architect) or Python

frameworks are highly preferred.

About Us:

Datum builds market intelligence solutions for the retail industry. We transform public and proprietary data into actionable insights that help retail brands decide where to expand, compete, and grow. We are a small, fast-moving team that works closely with customers and

believes in shipping impactful products quickly.

About the Role

We're looking for a Full Stack Platform Engineer to build and own our end-to-end product ecosystem, including:

● Data acquisition through scalable web scraping and ETL pipelines

● Customer-facing analytics platform

● Geospatial analysis engine powering retail insights

You'll work across frontend, backend, data engineering, cloud infrastructure, and geospatial systems while collaborating directly with the founder and customers.

Key Responsibilities

● Build scalable web scrapers and ETL pipelines

● Develop customer-facing features using React/Next.js

● Design REST & WebSocket APIs

● Work with PostgreSQL/PostGIS and geospatial data

● Own deployment, CI/CD, monitoring, and cloud infrastructure

● Translate customer feedback into product features

Must-Have Skills

● 3–6 years of Full Stack development experience

● Python (FastAPI/Django)

● React or Next.js with JavaScript/TypeScript

● Web scraping using Scrapy, Playwright, Selenium, or BeautifulSoup

● PostgreSQL (PostGIS preferred)

● REST APIs, JWT/OAuth

● Docker, Git, AWS/GCP/Azure

● Understanding of proxy rotation and anti-bot techniques

Good to Have

● Mapbox, Leaflet, or Google Maps Platform

● Airflow, Redis, Kafka, or SQS

● Experience with large-scale scraping (Google Maps, Zomato, Justdial, etc.)

● Geospatial analytics or retail domain experience

● Startup experience with end-to-end ownership

Title - Sr Engineering Manager

Location –Remote

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 22,000+ customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters that are doers, thinkers, and collaborators who embrace and live by our values:

• Invested Relationships
• Fiscal Prudence
• Candid Conversations

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 22,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit www.egnyte.com

The Monetization Infrastructure team is responsible for all the systems that power Egnyte’s back office: billing, customer intake, account lifecycle and many others. This highly crucial function combines strong business attachment with technical complexity due to Egnyte’s scale and strong pace of innovation.

WHAT YOU’LL DO:

• Lead the Monetization Infrastructure engineering group, reporting to the Platform Engineering VP.
• Be hands-on and lead from the front; provide technical inputs and direction to the group, acting as a check and balance on key technical decisions and helping shape technical direction. Participate and contribute to system designs and code reviews.
• Ensure high quality operation of the systems under your responsibility. Drive a culture of ownership and continuous operational improvement.
• Collaborate with key stakeholders, such as Finance, Product Management and other Engineering groups, to implement end-to-end use cases and support high quality of service.
• Champion fluent use of AI tools across the team and drive adoption of advanced AI-assisted software development lifecycle (SDLC) practices.

YOUR QUALIFICATIONS:

• Managed engineering teams of 15+ people in SaaS product companies, including experience leading managers.
• Hands-on: understand and be able to contribute to system designs. Past background as a staff engineer or architect with a track record of releasing widely adopted solutions.
• Past background in Python (mandatory) and Java (desirable).
• Understanding of cloud platforms (GCP, Azure or AWS) and infrastructure as code concepts is highly desirable.
• Experience in leading distributed teams.
• Fluent in applying AI tools across the engineering workflow, with a track record of driving advanced AI-driven SDLC adoption within a team.

BENEFITS:

• Competitive salaries
• Company equity depending on role and level
• Medical insurance and healthcare benefits for you and your family
• Fully paid premiums for life insurance
• Flexible hours and PTO
• Gym reimbursement
• Childcare reimbursement
• Group term life insurance

Equal Employment Opportunity

At Egnyte, we celebrate our unique differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Our global Egnyte Employee Communities (EECs) support representation and inclusion across our diverse workplace. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be. 

Any employees with questions or concerns about equal employment opportunities in the workplace are encouraged to bring these issues to the attention of hrategnyte.com. Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. If employees feel they have been subjected to any such retaliation, they should contact hrategnyte.com. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy. 

What You Will Own 

Platform Architecture 

• Full architectural ownership of the non-AWS toolchain: CI/CD, observability, event streaming, automation, secrets, and deployment infrastructure 
• Define, build, and enforce platform standards across portfolio products 
• Terraform IaC for all infrastructure — nothing provisioned manually, everything versioned and reviewed 
• Self-service developer platform so product teams ship without waiting on platform 

Event Streaming & Pipeline Infrastructure 

• Own the event streaming architecture, operational standards, and health monitoring across all products using real-time pipelines 
• Design and maintain batch processing infrastructure alongside live event flows 
• Ensure pipeline reliability, throughput, and cost are actively managed at scale 

CI/CD & Deployment 

• Build and maintain CI/CD pipelines (GitHub Actions) across all portfolio products 
• Automate triage and retry logic for known failure classes — flaky tests, dependency timeouts, OOM kills — so engineers are only paged for genuinely novel failures 
• Deployment standards: release management, rollback mechanisms, canary and blue-green patterns where justified 

Observability & Reliability 

• Own the full observability stack: Grafana, Prometheus, and Loki across all products 
• SLOs and error budgets defined per product; reliability tracked consistently 
• Build alerting that correlates signals and surfaces diagnostic context alongside notifications — so on-call engineers arrive at an incident with hypotheses, not a blank screen 
• Incident response: on-call design, escalation playbooks, post-mortem facilitation 
• Automated remediation scoped to a defined set of safe, idempotent actions — container restarts, ECS task scaling, known rollback patterns. Novel or ambiguous failures escalate to a human with full context attached 

Acquisition Onboarding 

• Platform audit and gap analysis for every new acquisition — assessing CI/CD maturity, IaC coverage, observability gaps, and security posture 
• Migration plan and execution for each portfolio company joining the platform.
• Target: full platform integration within a defined window per acquisition 

What We're Looking For 

Experience & Background 

• 8–12 years in platform engineering, DevOps, or SRE — with clear evidence of increasing ownership over time 
• Strong Terraform depth across multi-environment, multi-account setups 
• CI/CD ownership across a multi-product environment with GitHub Actions 
• Experience with event streaming infrastructure at production scale — design, operations, reliability, and cost management 
• Hands-on Grafana, Prometheus, and Loki in production 
• AWS operational depth: ECS, EKS, RDS, IAM, VPC, CloudWatch, Cost Explorer 
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortem culture 
• Acquisition or greenfield platform integration experience strongly preferred 

We’re on the hunt for a Principal Engineer who loves solving tough problems, mentoring others, and shaping the future of our platform. In this role, you’ll be leading the design and build of scalable systems and integrations across major cybersecurity platforms. Sometimes you’ll be deep in the code, other times you’ll be guiding teams and customers to the right solutions. If you enjoy balancing hands-on work with big-picture thinking, this could be your spot. 

About Us

At Metron Security, we help top cybersecurity companies supercharge their tools through automation and integrations. Our engineers connect and extend platforms like Splunk, IBM QRadar, ServiceNow, CrowdStrike, Cybereason, and many more. We believe in a developer-first culture where creativity, ownership, and continuous learning drive everything we do. 

Why You’ll Love Working Here

• A true developer-first environment where your ideas and technical chops matter.
• Hands-on exposure to 250+ security platforms (yep, really).
• Direct contact with customers so you can see the impact of your work right away.
• A fast-paced, growth-focused culture—but we also respect work-life balance. No weekends, and only occasional evening calls. 

What We’re Looking For 

We’re hoping to meet someone who has both deep technical expertise and natural leadership instincts. You think holistically about systems, enjoy digging into tricky problems, and can guide both teammates and customers to success.

Must-Have Skills

• Solid programming experience across multiple languages (Python, TypeScript, Java, Node.js, Angular, React, C#, C++… we’re language-agnostic and use the best tool for the job).
• Quick at learning new security platforms.
• Proven ability to design and build scalable systems, APIs, and integrations.
• Experience mentoring and leading engineering teams.
• Strong debugging and problem-solving skills in complex environments.
• Organized, reliable, and able to set and meet clear timelines.
• Comfortable working directly with customers to understand needs and design solutions.
• Familiar with cloud platforms (AWS, GCP, or Azure) and security best practices. 

Bonus Points If You

• Have experience building or leading integrations with enterprise security tools.
• Like approaching challenges with a “hacker mindset.” 
• Know your way around Docker, Kubernetes, and cloud deployments. 
• Contribute to open source or share technical insights publicly. 

What You’ll Do

• Be the face of Metron Security with our customers—collaborating on solutions and keeping communication clear.
• Bridge the gap between customers and our dev team, ensuring the right info flows both ways. 
• Mentor and train junior developers, helping them level up. 
• Step in to tackle tough technical problems when the team needs backup.
• Build and document knowledge about security platforms.
• Spot potential roadblocks early and help keep projects on track.

Who You Are

• Strategic thinker who isn’t afraid to roll up their sleeves.
• Clear communicator who collaborates openly.
• Proud of building strong, maintainable solutions that exceed expectations.
• Curious, quick learner, and always exploring new technologies.
• Positive, “let’s figure it out” teammate who lifts others up. 

At Metron Security, we’re all about helping security teams work smarter. If you’re excited to take on big engineering challenges, mentor others, and drive technical vision in a growing company, we’d love to talk.

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

We are a UK-based ecommerce company looking for a hands-on AI Automation & Integrations Engineer based in India to work directly with the founder.

Our goal is to progressively build an AI-first ecommerce operation by using AI, automation, APIs and software integrations to reduce manual work, improve decision-making and identify opportunities to increase revenue and profitability.

This is not a traditional data science or prompt engineering role. We are looking for a builder who can understand real business problems and turn them into reliable working systems.

What you will work on

• Build AI-powered automations and internal tools
• Connect ecommerce platforms and business systems through APIs and webhooks
• Build AI agents and LLM-powered workflows
• Automate repetitive operational processes
• Work with Shopify and ecommerce data
• Build automated reporting, alerts and business intelligence
• Develop inventory forecasting and operational tools
• Integrate AI with customer service, marketing, fulfilment and other business systems
• Identify new areas where AI and automation can improve efficiency, revenue or profitability
• Maintain and improve existing automations

Required skills

• Strong Python experience
• Strong understanding of REST APIs and webhooks
• Experience building software integrations and automations
• Practical experience using LLM APIs such as Claude, OpenAI or Gemini
• Experience working with databases such as PostgreSQL
• Git/GitHub
• Strong problem-solving ability
• Good written and spoken English
• Ability to work independently and take ownership of projects

Highly desirable

• n8n
• Shopify Admin API
• GraphQL
• JavaScript/TypeScript
• AI agents
• LangGraph/LangChain
• MCP
• AWS/GCP
• Ecommerce experience
• Data extraction/scraping
• Customer service or marketing integrations

We value real projects and practical ability more than certificates.

Candidates should be comfortable showing examples of AI automations, integrations, agents or software systems they have personally built.

Location: Remote, India

Experience: 3-7 years

Salary: ₹15-22 LPA depending on experience