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Artificial Intelligence Engineer

Recro

2 - 5 years

Bengaluru

Posted: 29/06/2026

Job Description

AI Engineer Agentic AI & Production ML

Experience

35 Years

Role Overview

We are looking for an AI Engineer to build and own production-grade AI systems end-to-end from LLM applications and agentic workflows to model serving, evaluation, and monitoring.

The role requires strong hands-on experience in Agentic AI, LLM orchestration, self-hosted models, and production ML engineering.

Responsibilities

Agentic AI & LLM Systems (Must Have)

  • Build AI agents, LLM workflows, and orchestration systems.
  • Develop RAG pipelines, memory systems, and retrieval workflows.
  • Work with LLM gateways and agent frameworks.
  • Improve reliability and performance of LLM applications.

Model Serving & Infrastructure (Must Have)

  • Deploy and optimize self-hosted AI models.
  • Experience with vLLM / Triton or similar serving frameworks.
  • Optimize latency, scalability, and inference cost.
  • Work with Docker, Kubernetes, and cloud infrastructure.

AI Engineering

  • Build production AI systems using Python.
  • Work with PyTorch, Hugging Face, Transformers, and vector databases.
  • Own AI lifecycle: development deployment monitoring improvement.

Evaluation & Observability

  • Build evaluation frameworks and benchmark datasets.
  • Track AI quality, latency, cost, and reliability metrics.
  • Set up monitoring, dashboards, and alerts for production AI systems.

Speech AI (Good to Have)

  • Experience with STT, ASR, speaker diarization, or voice AI systems.

Required Skills

Must Have

  • Agentic AI
  • LLM / Generative AI
  • LLM Orchestration
  • LLM Gateway
  • RAG
  • Vector Databases
  • Self-hosted Models
  • vLLM / Triton
  • Python
  • PyTorch
  • Hugging Face
  • Kubernetes
  • MLOps

Good to Have

  • Speech AI / STT
  • RLHF
  • Reinforcement Learning
  • AI Evaluation
  • Open-source AI contributions

Ideal Candidate Profile

  • Has shipped AI products into production.
  • Strong understanding of LLM systems and AI architecture.
  • Can own complete AI systems, not just model tuning.
  • Demonstrates strong engineering fundamentals and problem-solving ability.

Hiring benchmark: Candidates should demonstrate strong Agentic AI depth, production ML experience, and ownership of scalable AI systems.

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