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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