Senior Software Development Engineer

Company: Esper
Website: Visit Website
LinkedIn: Visit LinkedIn
Business Type: Startup
Company Type: Product & Service
Business Model: B2B
Funding Stage: Pre-seed
Industry: Software Development
Salary Range: ₹ 25-42 Lacs PA
Job Description
Senior Software Development Engineer
Bangalore - Engineering
Esper is experiencing hyper growth!
We are the industry pioneers in building technology that enables businesses to manage and operate massive fleets of edge devices at scale. Our cloud-native platform allows customers to seamlessly configure, deploy, and manage devices across multiple operating systems with reliability, security, and a high level of automation. Esper powers mission-critical device ecosystems to achieve operational excellence for some of the world's most innovative brands across retail, hospitality, logistics, and healthcare.
Our engineering team is AI-native by design. Agentic and AI-assisted workflows are embedded into how we build every day, enabling engineers to move faster and deliver higher-quality outcomes. We combine this with a strong foundation in engineering fundamentals and the judgment to know when to leverage AI and when human expertise is essential.
What We Think Makes Us Special
Esper is a fast-growing, well-funded company where everyone matters and you can see your impact daily. We trust our teammates and offer intense ownership and therefore accountability. We’re inventing the future and building something special. The team really enjoys what we do and cares about your input. We don’t hire just to fill a spot, we want you to make a difference.
The Role
We are seeking a Senior Software Development Engineer to architect and manage the high-scale backend services driving the Esper platform. You will lead technical initiatives from conceptual design through production operations, collaborating with cross-functional product and quality teams.
You will serve as a vanguard for engineering excellence by integrating agentic AI workflows into your daily practice. Crucially, you possess elite engineering fundamentals: you can architect, implement, and resolve complex issues independently, using AI as a force multiplier to ensure development speed never compromises quality.
Key Responsibilities
Core Infrastructure: Engineer and scale high-performance backend APIs and services using Python or Go for massive device fleets.
Full-Stack Velocity: Deliver seamless user experiences and operational dashboards utilizing React and TypeScript.
Adaptive Execution: Navigate the entire technical stack fluidly, employing AI-assisted workflows to bridge expertise gaps and maintain continuous delivery cycles.
Technical Leadership: Drive architectural design, uphold code quality standards through rigorous reviews, and mentor the broader engineering organization.
Cross-Functional Partnership: Work in tandem with Design, Product, and Success teams to build mission-critical, customer-centric features.
AI-Native Productivity Integration
Advanced IDEs: Masterfully apply AI-first development environments such as Claude Code, AWS Bedrock, OpenAI, among others to dramatically accelerate productivity.
Context Architecture: Utilize the Model Context Protocol (MCP) to provide AI agents with secure, precise access to local codebase metadata and infrastructure schemas.
Agentic Systems: Deploy autonomous Multi-Agent workflows that handle automated testing and full-stack scaffolding with self-correcting feedback loops.
Experience & Fundamentals
Professional Tenure: 4 to 8 years of experience building and scaling production-grade enterprise software.
Operational Ownership: Proven track record of managing live services, including incident response and observability enhancements.
Independent Judgment: Elite engineering intuition. You must be able to design and debug sophisticated systems without AI reliance, serving as the final authority on code correctness.
Requirements
Languages & DB: Deep expertise in Python or Go, alongside relational data modeling (Postgres preferred).
Architecture: Thorough understanding of microservices and distributed systems patterns.
Cloud Infrastructure: Hands-on experience with AWS, GCP, or Azure environments.
Platform Ops: Proficiency with Docker and Kubernetes, coupled with robust CI/CD pipelines.
Streaming: Experience with message brokers such as Kafka or SQS.
AI Tooling: Exposure to frameworks like LangChain or Bedrock Agents for dev-cycle automation.
Workflow: Mastery of Git and collaborative engineering best practices.
Bonus
Background in mobile ecosystem development (Android or iOS).
Exposure to Device Management and/or IoT platforms.

Work arrangement
Hybrid