---
title: "Akhil Sanker - Software Development Engineer 2 in Bengaluru | Tal"
description: "Meet Akhil Sanker, SDE-2 @Amazon | Backend & Infrastructure | Distributed Systems | Cloud (AWS, Azure) | Generative AI based in Bengaluru. AI stack includes antigravity, opencode, and claudecode. Explore public work links including github."
image: "https://tal.club/meet/akhil-sanker/share-image"
---

# Akhil Sanker on Tal

## Headline

SDE\-2 @Amazon \| Backend & Infrastructure \| Distributed Systems \| Cloud \(AWS, Azure\) \| Generative AI

## About

I’m a backend and infrastructure engineer who enjoys working on systems that have real constraints: scale, latency, cost, and reliability, and making them work in production\. Most of my work revolves around designing and operating distributed backend systems, improving performance, and building cloud infrastructure that scales\. I’ve spent a lot of time working around slow APIs, fixing data access bottlenecks, and turning systems that “mostly work” into stable, observable, and easier ones\. I’ve owned and led backend systems across finance, enterprise SaaS, and life sciences\. That work has included building low\-latency APIs, scaling data\-heavy backends, designing event\-driven and batch processing workflows, and operating production infrastructure on AWS and Azure\. Areas I work deeply in include: \- Distributed backend systems and API design \- Performance optimization, caching, and data access patterns \- Cloud infrastructure and production operations \(AWS, Azure\) \- Relational and NoSQL databases at scale \- Observability, reliability, and cost\-aware system design Alongside core backend and infrastructure work, I’ve also integrated machine learning and generative AI systems into production backends \- including RAG\-based workflows and ML\-powered services \-focusing on use cases where they provide clear, measurable value rather than being run as experiments\. I’m especially effective in messy, complex systems: diagnosing where things slow down, understanding why they fail under load, and simplifying architectures to make them faster, more predictable, and easier to maintain\. At the moment, I’m continuing to go deeper into distributed systems, backend performance engineering, cloud infrastructure, and production\-grade GenAI integration, with a strong bias toward decisions that scale both technically and operationally\.

## Location

Bengaluru

## AI stack

antigravity

opencode

claudecode

## Work experience

Software Development Engineer 2 at Amazon, Jun 2026 \- Present · 3 mos, Bengaluru

Software Engineer 2 at Parspec, May 2025 \- Jun 2026 · 1 yr 2 mos, Bengaluru, Developing backend systems focused on performance and reliability initiatives across high\-traffic core services, data integrity, latency reduction, and operational resilience\. Designed and implemented a production\-grade idempotency layer using DynamoDB for critical compilation workflows, eliminating duplicate processing and ensuring transactional safety\. Owned the full lifecycle, including architecture, cost analysis, and production data migration\. Re\-architected a legacy, high\-volume API suite handling millions of records, removing systemic N\+1 query bottlenecks and introducing strategic caching and abstraction layers\. Reduced p99 latency from >20s to <1s\. Implemented a centralized caching and invalidation framework using Valkey, improving read performance and consistency across multiple backend modules\. Built event\-driven webhook pipelines to stream real\-time quote events to external systems, enabling non\-blocking, high\-throughput processing within a synchronous Django ecosystem\. Improved production observability by setting up CloudWatch alarms and custom New Relic dashboards, enabling proactive detection of performance regressions and infrastructure bottlenecks\. Still ongoing \.\.\.\.\.\.\.

Software Engineer 2 \| SSE 1 at Bajaj Finserv, Jul 2024 \- May 2025 · 11 mos, Pune, Maharashtra, India, Architected and scaled cloud\-native backend systems on Azure \(Functions, App Services, Cosmos DB\) for high\-traffic financial applications, improving system availability and reducing downtime by \~15%\. Designed and deployed REST APIs using FastAPI and Node\.js, achieving \~30% improvement in response times through better service boundaries and data access patterns\. Implemented OAuth 2\.0–based authentication flows supporting mobile and web platforms, ensuring secure and consistent identity handling across services\. Built and operated containerized workloads on Kubernetes \(self\-managed on Linux\), implementing horizontal scaling and batch\-based processing for compute\-heavy workflows\. Optimized MongoDB performance through indexing and batching strategies, reducing critical query execution times by \~40%\. Led CI/CD modernization using Azure DevOps, introducing linters, security scans, and DevSecOps practices, resulting in fewer deployment failures and faster release cycles\. Mentored and led a team of junior engineers while driving the architecture and delivery of the EFA platform, contributing to 100K\+ monthly user growth\.

Software Engineer at Bajaj Finserv, Jul 2022 \- Jul 2024 · 2 yrs 1 mo, Pune, Maharashtra, India, Developed backend systems and data pipelines across Azure and GCP ecosystems, supporting analytics, authentication, and event\-driven workflows\. Built scalable ingestion and transformation pipelines using PySpark, integrating processed data into Snowflake for centralized analytics\. Implemented CDC\-style data flows and analytics integrations for user activity tracking across platforms\. Contributed to backend architecture design, infrastructure automation, and system reliability improvements in production environments\.

Software Engineer Intern at Bajaj Finserv, Jan 2022 \- Jul 2022 · 7 mos, Pune, Maharashtra, India, Worked on backend services and cloud\-based data workflows, contributing to production systems used by internal and external consumers\. Assisted in building REST APIs, analytics integrations, and cloud infrastructure components under senior engineer guidance\.

Backend \| Cloud & ML Engineer at Medvolt, May 2021 \- Jan 2022 · 9 mos, Remote, Acted as a founding engineer, owning backend architecture, cloud infrastructure, and early ML integrations from prototype to production\. Designed and deployed a high\-performance AWS\-based compute framework using EC2, Batch, ECS, and Step Functions, reducing simulation runtimes by \~60% through parallelization and resource tuning\. Built fault\-tolerant, auto\-scaled infrastructure achieving 99\.99% uptime using ELB and Auto Scaling\. Developed high\-concurrency backend systems using FastAPI and Django, supporting \~200 RPS on a single node through efficient async and caching strategies\. Implemented CI/CD pipelines with GitHub Actions and AWS CodePipeline, enabling multiple zero\-downtime deployments per day\. Reduced cloud costs by \~50% through aggressive optimization using Spot/Reserved Instances and VPC\-level traffic routing improvements\. Integrated ML models \(TensorFlow, OpenAI\) into production workflows for drug discovery use cases, accelerating candidate evaluation and improving prediction accuracy\. Helped convert academic research into a commercial SaaS platform\.

Machine Learning Engineer at Omdena, Aug 2020 \- Aug 2021 · 1 yr 1 mo

## Education

Bachelor of Technology \- BTech, Computer Science Engineering with Specialization in Artificial Intelligence and Machine Learning, SRM IST Chennai

School, Mathematics and Computer Science, Army Public School \(APS\)

## Public links

- github: https://github\.com/akhilmedvolt

[View the original profile](https://tal.club/meet/akhil-sanker)

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