# Senior Software Engineer

**Company:** [Weekday AI](http://jobs.workable.com/companies/pxG9rDgnvZm2c86JUchT1j.md)
**Location:** Bengaluru, India
**Workplace:** on site
**Employment type:** Full-time
**Department:** Weekday's Client via platform

[Apply for this job](http://jobs.workable.com/view/73d1d573-911f-4609-b7da-bcbd8ea048b4)

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟯𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟯𝟱-𝟱𝟬 𝗟𝗣𝗔)

Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are seeking a highly skilled **Senior Software Engineer – Backend** to design, build, and scale next-generation AI platform services that power enterprise-grade intelligent applications. This role is ideal for engineers with strong expertise in **Java, cloud-native microservices, distributed systems, and AI platform architecture**, along with hands-on experience integrating Large Language Models (LLMs), agent orchestration frameworks, and modern backend technologies.

As a senior member of the engineering team, you will own the development of scalable backend services, AI gateways, and orchestration frameworks while collaborating with cross-functional teams to deliver secure, reliable, and high-performance solutions. The role demands strong technical leadership, excellent problem-solving skills, and a passion for building production-ready AI-powered platforms.

## Requirements

### Key Responsibilities

-   Design, develop, and maintain production-grade backend services for AI platforms, including LLM gateways, model integration services, and agent orchestration frameworks.
-   Build scalable cloud-native microservices using Java, Spring Boot, Kafka, and modern distributed system design principles.
-   Architect and implement AI gateway capabilities such as multi-provider model routing, intelligent failover, token management, cost optimization, request logging, and observability.
-   Develop infrastructure supporting Model Context Protocol (MCP), tool integration, and intelligent agent workflows.
-   Design and implement multi-step AI reasoning workflows, tool orchestration, guardrails, and human-in-the-loop processes for enterprise AI applications.
-   Take end-to-end ownership of critical backend components, ensuring scalability, security, reliability, and maintainability.
-   Diagnose and resolve complex performance bottlenecks across backend services, AI inference layers, and distributed architectures.
-   Collaborate with Product, AI/ML, QA, UX, and Engineering teams to design and deliver high-quality software solutions.
-   Mentor junior engineers through technical guidance, code reviews, architecture discussions, and engineering best practices.
-   Promote software quality through clean code, automated testing, performance optimization, and continuous improvement initiatives.

### What Makes You a Great Fit

-   5+ years of professional experience in **backend software engineering** with strong expertise in **Java** and object-oriented programming.
-   Proven experience building and scaling **cloud-native microservices** and enterprise backend applications using **Spring Boot**, Kafka, and distributed architectures.
-   Strong understanding of relational and NoSQL databases, including **MySQL**, **MongoDB**, and modern data management practices.
-   Experience developing enterprise-scale applications with strong knowledge of performance tuning, debugging, monitoring, and backend optimization.
-   Hands-on experience with cloud platforms such as **AWS** and familiarity with observability tools, logging frameworks, and monitoring solutions.
-   Solid understanding of **Large Language Models (LLMs)**, AI platform architecture, and intelligent application development.
-   Experience or strong knowledge of **Model Context Protocol (MCP)**, AI gateways, multi-model routing, semantic caching, and AI service orchestration.
-   Familiarity with agentic AI frameworks such as **LangChain**, **LangGraph**, **LlamaIndex**, **CrewAI**, **OpenAI Agents SDK**, or similar orchestration technologies.
-   Understanding of AI observability, evaluation techniques, prompt execution monitoring, AI safety practices, content filtering, and hallucination mitigation.
-   Excellent analytical thinking, communication, mentoring, and collaboration skills with the ability to thrive in a fast-paced engineering environment while delivering high-quality, production-ready solutions.