Open to opportunities

Sandeep

@sandeep

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Lead Engineer and Team Lead building scalable Python/Django platforms and AI workflow products that ship end-to-end.

India

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What I'm looking for

I want to lead the architecture and delivery of scalable Python/Django products—especially AI workflow platforms—working with agile teams to ship measurable performance wins, strong security/auth, and real-time, async backend systems.

Team Lead with 8 years of experience designing, building, and shipping full-stack products end-to-end across logistics, e-commerce, wellness, and fintech/investment technology domains. Currently sole architect and lead developer of Spheresmith, an AI-powered MAAS (Memo as a Service) platform for deal and investment workflows, built with Next.js, React 19, Django 5.2, Django REST Framework, Celery, Redis, PostgreSQL, and WebSocket real-time architecture. Proven track record of 80% performance improvements, configurable rule engine design, enterprise authentication (OIDC, SAML, Azure AD, JWT), and leading agile engineering teams. Specialises in Python, Django, REST API design, microservices, and scalable backend systems

Experience

Work history, roles, and key accomplishments

Current

Software Development Engineer

Current

Fynd

Sep 2022 - Present (3 years 8 months)

Specialized in e-commerce logistics with expertise in Python, Sanic, Docker, Kubernetes, Kafka, MongoDB, AWS. Streamlined product splitting, optimized delivery algorithms, and enhanced partner selection. Improved Docker efficiency, introduced serviceability features, and re-engineered the Store Selection module for an 80% performance boost.

Python Sanic Docker Kubernetes Kafka MongoDB Prometheus Redis

Senior Software Engineer

Zenoti

Jun 2021 - Aug 2022 (1 year 2 months)

Senior Software Engineer in wellness industry. Integrated analytics, automated offline conversion uploads, AWS-powered smart campaigns, API-driven location and review system, and improved UX with AngularJS

Google Analytics Facebook Pixel Google Tag Manager Python AWS

Software Engineer

Janio Asia

Feb 2021 - May 2021 (3 months)

At Jane Asia, I automated email communications, optimized order APIs, and spearheaded efficient order tracking using Python, Django, AWS, and Postgres.

Python Django AWS Postgres

Product Engineer

Loyalty Juggernaut

Jun 2018 - Feb 2021 (2 years 8 months)

At Loyalty Juggernaut, I developed rule-based Point Expiration, member-brand interaction, and currency conversion services. Led AWS QuickSight reporting, created a dynamic Django framework, synchronized data with Mailchimp, and streamlined email communication. Led a small agile team

Python Django AWS Postgres Redis Celery Docker Datadog

Current

Lead Engineer

Current

Spheresmith

Nov 2024 - Present (1 year 6 months)

Built and deployed a full-stack AI investment platform using Next.js, Django/DRF, Docker, Nginx, Celery, Redis, and WebSockets. Delivered AI deal-to-memo generation, collaborative review workflows, RBAC workspaces, checklist/scoring engines, fund workflows, large-file ingestion/export, enterprise SSO (Google, Okta, Azure AD, SAML), and cloud storage integrations with AWS S3/GCS.

Python Django PostgreSQL Kubernetes GCP Databricks

Current

Lead Engineer & Team Lead

Current

Spheresmith

Nov 2024 - Present (1 year 6 months)

Sole architect and lead developer of Spheresmith, an AI-powered Memo as a Service platform, delivering end-to-end full-stack workflows for investment deal-to-memo generation and collaborative review. Improved performance by 80% and built enterprise authentication (OIDC/SAML/JWT) plus async real-time processing using Celery, Redis, and WebSockets.

Python Django REST Framework Celery Redis PostgreSQL Next.js Nginx

Software Development Engineer II

Fynd (Reliance Retail)

Sep 2022 - Aug 2024 (1 year 11 months)

Re-engineered the Store Selection module, delivering 80% performance improvement via architectural and business-logic enhancements for accuracy, scalability, and extensibility. Built partner orchestration with a rule engine for serviceability-based selection, along with expected-delivery-date algorithms and data aggregation at scale.