Senior Software Engineer (Java/Go + AI) |Core Engineering Meets Real LLM Systems | Billion-Dollar AI Platform

  • 25 Lakhs
  • Bengaluru
Job Details
Full Time 3–6 years
Skills

Full Job Description

About the Company

A billion-dollar, AI-native B2B SaaS platform built for large, global enterprises. The platform supports customer-facing operations through a unified AI architecture designed for scale, reliability, and real business outcomes.

The technology combines Generative AI, Knowledge AI, Emotion AI, workflow automation, and AI copilots to enable intelligent, human-centered customer and employee experiences. Operating at enterprise scale across industries, the platform processes voice, video, and text data to power mission-critical systems.

As AI continues to reshape enterprise operations, the focus remains on building the connective layer between people, machines, and data through production-ready, scalable systems.

Role: Senior Software Engineer (Java/Go with AI)

This role sits within Product Engineering and focuses on designing, building, and operating scalable software systems that power core SaaS and AI-driven capabilities. It is a hands-on engineering role with ownership across backend services, APIs, and applied AI integrations.

The role involves close collaboration with product managers, designers, and engineers across regions to translate product requirements into robust technical solutions. It suits engineers who enjoy building real-world systems, shipping features end to end, and working with applied AI in production environments.

Responsibilities

  • Design, develop, test, and maintain scalable backend and frontend components for enterprise-grade SaaS applications

  • Translate business and product requirements into clear technical designs and implementation plans

  • Contribute to system and API design with a focus on performance, maintainability, and scalability

  • Build and integrate LLM-powered features such as RAG pipelines, vector search, and AI-driven workflows

  • Write clean, well-documented, and testable code following engineering best practices

  • Participate in peer code reviews and provide constructive feedback

  • Collaborate with cross-functional and multi-region teams to deliver features within agreed timelines

  • Improve existing systems through refactoring, optimization, and bug fixes

  • Follow Agile development practices and contribute to continuous engineering improvements

Requirements

  • 3–6 years of professional software development experience

  • Strong programming skills in Java or Go (experience with Python or Rust is a plus)

  • Solid experience building backend systems using modern frameworks and libraries

  • Hands-on experience with APIs and protocols such as REST, WebSockets, and gRPC (familiarity with MCP is a plus)

  • Experience working with relational or document databases such as PostgreSQL or MongoDB

  • Strong understanding of microservices architectures and distributed systems fundamentals

  • Good foundation in data structures, algorithms, and system design

  • Experience building or integrating LLM-based features, including RAG and vector search

  • Familiarity with agent frameworks such as LangChain or LangGraph

  • Experience working with distributed or multi-region teams

  • Strong analytical and problem-solving skills with attention to code quality

Good to Have

  • Experience with messaging and data infrastructure such as Kafka, Redis, or ClickHouse

  • Hands-on experience in Linux environments

  • Exposure to multiple data paradigms: SQL, NoSQL, time-series, or graph databases

  • Experience deploying and operating AI/ML or LLM-powered services (MLOps / LLMOps)

  • Familiarity with observability for AI systems, including logging, tracing, monitoring, and evaluation

  • Exposure to LLM fine-tuning techniques such as LoRA, QLoRA, or instruction tuning

Why This Role Stands Out

  • Opportunity to work on production-grade AI systems, not experimental projects

  • Exposure to enterprise-scale SaaS platforms with global impact

  • Combination of core software engineering and applied AI in real-world use cases

  • Collaboration with distributed teams solving complex, high-impact problems

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