AI Engineer

AI Engineer – Agentic AI & Production ML

Experience

3–7 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.