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Senior Software Engineer – AI/ML & Agentic Systems

L&T Technology Services
Hyderabad, IND
Full-time
Mid-Senior
Onsite
Discovered 1 weeks ago
PythonAI agents and multi-agent systemsMachine learningPyTorchTensorFlowScikit-learn
Free

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PythonAI agents and multi-agent systemsMachine learning
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Role Overview

Senior Software Engineer role focused on AI/ML and agentic systems.

The role supports automation, test generation, failure analysis, and production AI solutions.

The stated location is Bangalore or Hyderabad, as applicable.

Experience and Education

  • Requires 5–8 years of professional experience.
  • Requires a bachelor’s or master’s degree in Computer Science, Electrical and Electronics Engineering, or a related field.

Core Skills

  • Python programming, AI agents, multi-agent systems, and machine learning using PyTorch, TensorFlow, or Scikit-learn.
  • LLMs, prompt engineering, RAG, LangChain, and AutoGen.
  • FastAPI or Flask, Snowflake, SQL, MySQL, MLOps, model deployment, and Linux/Unix.
  • C++ is preferred.

Job Responsibilities

  • Design and deploy AI agents and multi-agent workflows for automation, test generation, and failure analysis.
  • Build, train, and optimize models for anomaly detection, predictive analytics, and test optimization.
  • Develop scalable LLM and RAG solutions and integrate AI systems with enterprise databases and data pipelines.
  • Develop production-grade Python backend applications.
  • Implement MLOps practices for model deployment, monitoring, and lifecycle management.
  • Collaborate with engineering teams on integration and knowledge transfer.

Preferred Experience

  • Hands-on experience with LangChain, AutoGen, or similar AI agent frameworks.
  • Strong expertise in LLM APIs, prompt engineering, and RAG pipelines.
  • Experience deploying machine-learning models in production environments.
  • Proficiency in FastAPI or Flask API development.
  • Strong understanding of Linux environments, infrastructure automation, and backend engineering.
  • Knowledge of FPGA, validation, or test automation environments is advantageous.

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