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Agentic AI Engineer; RAG & LLM Systems

Job in 201301, Noida, Uttar Pradesh, India
Listing for: BIG Language Solutions
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 1200000 - 1500000 INR Yearly INR 1200000.00 1500000.00 YEAR
Job Description & How to Apply Below
Position: Agentic AI Engineer (RAG & LLM Systems)
Position Name:
Agentic AI Engineer (RAG & LLM Systems)

Department: IT

Location:

Remote/Hybrid(Noida)

Employment Type:

Full-time / Contract

Compensation: 12-15 LPA(Based on the experience and interview)

Reports To:

VP of Artificial Intelligence

Role

Build and operate agentic AI systems for an interpretation and translation business, with direct ownership of RAG pipelines and agent workflows aligned to real business processes.

Responsibilities

• Design and implement RAG-based LLM systems for translation and interpretation workflows

• Build agentic solutions using Lang Chain, Microsoft Auto Gen, and CrewAI, and others

• Translate business processes into AI agent workflows (intake, knowledge retrieval, decisioning, output)

• Own end-to-end AI solution delivery from requirements to production

• Business Process Understanding & Optimization:
Analyze existing interpretation and translation workflows, identify inefficiencies, and design agentic AI solutions that measurably improve accuracy, turnaround time, and operational scalability.

• Work closely with business, Operations, and product stakeholders to clarify requirements and iterate

• Communicate technical tradeoffs, limitations, and outcomes clearly to non-technical teams

Requirements

• Strong experience with LLMs and production-grade RAG architectures

Hands-on experience with vector databases (Pinecone, FAISS, Weaviate, or equivalent)

• Proficiency in Python

• Experience deploying AI systems to production

• Demonstrated ability to understand business workflows and convert them into technical designs

• Comfortable with frequent stakeholder communication and requirement refinement

Nice to Have

• Experience in translation, interpretation, or multilingual NLP

• Familiarity with speech-to-text or text-to-speech systems

• Cloud experience (AWS, GCP, or Azure)

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