Salary
≈ $25k – $71k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp
Overview
Company
Impact
Profile match
Patch Infotech is a leading software service and product-based company that caters to a range of business verticals by providing full-suite technology solutions across web, mobile, and backend products.
We are looking for experienced AI Engineers with hands-on expertise in building and deploying production-grade AI solutions using Large Language Models (LLMs), LangGraph, Python, and Retrieval-Augmented Generation (RAG). The ideal candidate should have experience designing scalable, reliable, and enterprise-ready AI applications.
Responsibilities:
- Design and develop AI-powered applications using LLMs and agentic workflows.
- Build and maintain LangGraph-based state machines and multi-agent workflows.
- Develop and optimise RAG pipelines, including document ingestion, chunking, embeddings, vector databases, and retrieval strategies.
- Design structured outputs using Pydantic or similar frameworks.
- Implement intelligent workflows with confidence scoring, evaluation mechanisms, and human-in-the-loop capabilities.
- Build AI solutions integrated with enterprise systems and APIs.
- Develop deterministic unit tests and evaluation frameworks for LLM outputs.
- Collaborate with cross-functional teams to design scalable AI architectures and document technical solutions.
Requirements:
- 4+ years of experience building production AI/ML applications.
- Strong proficiency in Python.
- Hands-on experience with Large Language Models (LLMs) and Generative AI.
- Strong experience with LangGraph, including workflow orchestration, conditional routing, and state management.
- Experience building production-grade RAG pipelines.
- Hands-on experience with vector databases such as pgvector, Pinecone, Weaviate, or similar.
- Experience with Pydantic or equivalent structured output frameworks.
- Knowledge of prompt engineering, AI evaluation, and testing methodologies.
- Strong problem-solving and communication skills.
Good to Have:
- Experience with LangSmith or similar LLM observability tools.
- Experience with graph processing libraries such as NetworkX.
- Experience with Microsoft Teams Bot Framework.
- Knowledge of cloud platforms (Azure, AWS, or GCP).
- Familiarity with SRE, incident management, or FinOps concepts.
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