GenAI Engineer - LLMs, RAG & Orchestration

Senovo IT Ltd; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Senovo IT Ltd is seeking an experienced AI Engineer to join a FinTech project focused on designing, developing, and deploying advanced AI solutions. You will build scalable GenAI applications and intelligent workflows across enterprise systems.

The role emphasizes LLMs, RAG pipelines, LangChain and LangGraph, and production-grade MLOps practices to ensure secure, reliable deployments.

Qualifications

• 6+ years of professional software development experience.
• Strong expertise in Python.
• Hands-on with LLMs, RAG, LangChain, LangGraph.
• Experience building and deploying production AI applications.
• Knowledge of prompt engineering, vector databases, and semantic search.
• Experience integrating AI services and APIs.
• Fluent English and strong problem-solving/communication skills.

Responsibilities

• Design, develop, and deploy AI-powered applications using Python.
• Build and optimize LLM-based solutions.
• Develop and maintain RAG pipelines.
• Implement agent-based AI systems and orchestration frameworks.
• Work with LangChain and LangGraph to create scalable AI workflows.
• Integrate AI solutions into existing enterprise systems.
• Monitor, evaluate, and improve model performance, quality, reliability.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Follow best practices for MLOps, testing, security, and production deployment.

Skills

6+ years

Python

LLMs

RAG

LangChain

LangGraph

Agentic Orchestration

Production AI

Prompt Engineering

Vector DBs

Semantic Search

API Integration

Job description

Senovo IT Ltd is seeking an experienced AI Engineer to join a FinTech project focused on designing, developing, and deploying advanced AI solutions. You will build scalable GenAI applications and intelligent workflows across enterprise systems.

The role emphasizes LLMs, RAG pipelines, LangChain and LangGraph, and production-grade MLOps practices to ensure secure, reliable deployments.