Principal Software Engineer

Posted Yesterday
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
6M-9M Annually
Expert/Leader
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design and build scalable backend systems, distributed infrastructure, and agentic AI frameworks. Integrate and deploy LLMs into production, implement real-time and batch inference pipelines, MCP servers, RAG with vector databases, and MLOps/DevOps practices (CI/CD, observability, autoscaling). Optimize performance, reliability, and security, and collaborate across teams to improve AI platform architecture.
Summary Generated by Built In

This role is for one of the Weekday's clients

Salary range: Rs 5500000 - Rs 9000000 (ie INR 55-90 LPA)

Experience: 10+ yrs

Location: Bengaluru, Karnataka

Job Type: Full-Time

We are looking for a highly skilled AI Engineer to design, build, and optimize scalable backend systems and intelligent agentic frameworks that power advanced AI applications. In this role, you will work at the intersection of backend engineering, distributed systems, and Generative AI, enabling the deployment of high-performance AI services and intelligent workflows across production environments.

As an AI Engineer, you will collaborate with machine learning engineers, platform teams, and infrastructure specialists to build robust AI platforms, integrate large language models into production, and develop scalable inference pipelines. This role is ideal for professionals who are passionate about distributed AI systems, agentic architectures, and building reliable, production-ready AI solutions.


RequirementsKey Responsibilities
  • Design and develop scalable backend systems, microservices, and APIs using Python for AI-driven applications.
  • Architect distributed infrastructure capable of supporting high-throughput AI workloads and intelligent agent coordination.
  • Collaborate with machine learning teams to integrate and deploy trained models into production environments.
  • Build and maintain real-time and batch inference pipelines for AI-powered applications and services.
  • Develop and optimize AI agent frameworks using modern orchestration technologies and large language models.
  • Implement and manage Model Context Protocol (MCP) servers to enable seamless communication between AI agents and external tools.
  • Design and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge retrieval systems.
  • Contribute to MLOps and DevOps initiatives by implementing CI/CD pipelines, monitoring, observability, autoscaling, and infrastructure automation.
  • Optimize system performance, scalability, reliability, and security across AI infrastructure and model-serving environments.
  • Collaborate with cross-functional engineering teams to continuously improve AI platform architecture and operational efficiency.
What Makes You a Great Fit
  • Strong professional experience building production-grade applications using Python.
  • Expertise in Large Language Models (LLMs) and Generative AI technologies with hands-on experience deploying AI-powered solutions.
  • Deep understanding of distributed systems, system design, asynchronous programming, and network architecture.
  • Experience building AI agents using frameworks such as LangChain or similar agent orchestration platforms.
  • Strong knowledge of Model Context Protocol (MCP) and building interoperable AI agent ecosystems.
  • Hands-on experience with vector databases such as FAISS, Pinecone, or Weaviate for knowledge retrieval and RAG implementations.
  • Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or JAX and model-serving platforms including Triton Inference Server, TorchServe, ONNX Runtime, or Ray Serve.
  • Proficiency with Docker, Kubernetes, cloud platforms (AWS, Azure, or GCP), Infrastructure as Code, and modern CI/CD practices.
  • Experience working with SQL/NoSQL databases, Redis, Kafka, RabbitMQ, and scalable backend architectures.
  • Strong analytical, problem-solving, and collaboration skills with a passion for building secure, scalable, and production-ready AI systems.
  • Exposure to multi-agent systems, AI safety, advanced LLM architectures, or open-source AI projects is an added advantage.

Skills Required

  • 10+ years professional experience
  • Production-grade application development using Python
  • Expertise with Large Language Models and Generative AI and deploying AI solutions
  • Deep understanding of distributed systems, system design, asynchronous programming, and network architecture
  • Experience building AI agents using LangChain or similar agent orchestration frameworks
  • Knowledge and experience with Model Context Protocol (MCP)
  • Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) and RAG implementations
  • Familiarity with ML frameworks and model-serving platforms (PyTorch, TensorFlow, JAX, Triton, TorchServe, ONNX Runtime, Ray Serve)
  • Proficiency with Docker, Kubernetes, cloud platforms (AWS, Azure, or GCP), Infrastructure as Code, and CI/CD practices
  • Experience with SQL/NoSQL databases, Redis, Kafka, RabbitMQ, and scalable backend architectures
  • Exposure to multi-agent systems, AI safety, advanced LLM architectures, or open-source AI projects
Am I A Good Fit?
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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