AI Engineer, India, 2-3 years
At a glance
Mid-level AI Engineering role at Fa Ewjt Saasfaprod1. Noida · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and refine LLM agents that use tools, retrieval and coordinated workflows to tackle practical problems
- Develop ML pipelines for data handling, feature creation, model training and evaluation, then put them into use
- Link agents with cloud services, company systems and external tools so they can plan and complete tasks
- Shape end-to-end workflows with product, engineering and domain experts, improving safety and reliability
What you bring
- At least two years of practical Python experience and familiarity with PyTorch or TensorFlow
- At least one year with LangChain or LlamaIndex, plus one year building RAG pipelines and using vector databases
- Hands-on experience with agent or LLM systems, including tool use, task execution, orchestration, reasoning, prompts and API connections
- Experience deploying ML systems with cloud platforms, Docker, CI/CD and data pipelines
Who this fits
This role suits an AI engineer with two to three years of experience who can translate business needs into intelligent workflows and work across teams. It is a hybrid position in Noida, India.
From the employer
AI Engineer, India, 2-3 years
• Design, build, and optimize agentic AI systems leveraging LLMs, multi-agent frameworks, tool‑use orchestration, retrieval systems, and autonomous workflows to solve complex real‑world problems.
• Develop scalable ML pipelines and infrastructure including data processing, feature engineering, model training/evaluation and deployment using modern ML-Ops practices (Docker, Kubernetes, CI/CD, observability).
• Integrate agents with enterprise tools and APIs enabling autonomous planning, reasoning, and execution chains across cloud platforms, internal systems, and third‑party services.
• Collaborate cross‑functionally with product, engineering, and domain SMEs to design end‑to‑end intelligent workflows, ensure reliability/safety, and translate business needs into production‑grade agentic solutions.
• Minimum 2 year(s) of hands-on experience with Python (comfortable with PyTorch/TensorFlow)
• Minimum 1 year(s) of experience with LangChain/LlamaIndex
• Minimum 1 year(s) of experience with RAG pipelines and vector databases
• Practical exposure to agentic/LLM systems such as tool‑calling, autonomous task execution, workflow orchestration, reasoning chains, prompt engineering, and integrating models with APIs or enterprise systems.
• Strong MLOps & engineering discipline including experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), CI/CD, data pipelines, and deploying ML systems into production environments.
• Problem‑solving mindset and cross‑functional communication skills with the ability to translate business requirements into intelligent workflows, run experiments, and iterate quickly in a fast-paced AI environment.