Artificial Intelligence Engineer

Pi Square Technologies; Bengaluru; Hybrid; INR 2,400,000 - 4,000,000; Full time

Job summary

Pi Square Technologies in Bengaluru is seeking an AI Engineer with 3–5 years of hands-on experience to design, build and deploy scalable AI-powered applications, LLMs and agentic AI frameworks. You will deliver production-ready APIs and work with cross-functional teams on reliable, business-driven AI products.

The role emphasizes building intelligent systems, optimizing latency and cost, and deploying cloud-hosted AI solutions in a hybrid work model (3–4 days a week from the Bangalore office).

Qualifications

• 3+ years building and shipping LLM apps.
• Experience with agentic AI development.
• Strong Python/SQL and GenAI experience.
• BGV/background verification required.

Responsibilities

• Develop AI agents with tool-calling, memory, guardrails and structured outputs.
• Design RAG pipelines, prompt strategies and context management.
• Containerize and deploy solutions as REST APIs.
• Collaborate with product managers, data scientists and backend engineers.

Skills

Python

SQL

GenAI frameworks

Agentic Design

RAG architectures

REST APIs

Docker

Kubernetes

Cloud platforms

LangSmith

Tools

Docker

Kubernetes

FastAPI

LangChain

LangGraph

CrewAI

AutoGen

Pinecone

Qdrant

Chroma

Weaviate

Job description

Key Details

• Drive Date: October 10th
• Mode: In-Person Drive
• Drive Location: Hyderabad
• Offer Process: On-the-Spot Offers for eligible candidates on the same day.
• Work Mode: Hybrid model, 3-4 days per week from the Bangalore office.
• Experience: 4.5+ years
• Notice Period: Immediate to a maximum of 45 days

We are looking for an AI Engineer with 3 to 5 years of experience to design, build, and deploy scalable AI-powered applications, Large Language Models (LLMs), and Agentic AI frameworks.

In this role, you will focus on building intelligent systems, creating production ready APIs, and deploying cloud-hosted AI solutions.

You will collaborate with cross functional teams to translate emerging generative AI techniques into reliable, business driven products.

Key Responsibilities

Agentic AI & LLM Development

• Build, evaluate, and optimize AI agents using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
• Implement agentic workflows, multi-agent orchestration, tool integration, state management, and multi-step reasoning patterns (e.g., ReAct).
• Design robust Retrieval-Augmented Generation (RAG) pipelines, prompt tuning strategies, and context management systems.
• Integrate, fine-tune, or adapt both open-source (e.g., LLaMA, Phi) and commercial foundation models (e.g., GPT-4, Claude).

Deployment & MLOps

Package AI models and agentic workflows into production-ready REST APIs.

• Containerize and deploy solutions using Docker and Kubernetes across cloud platforms (AWS, Azure, or GCP).
• Establish MLOps pipelines covering model tracking, automated deployment (CI/CD), observability, and vector database management.
• Optimize system latency, token usage, and infrastructure cost for production workloads.

Cross-Functional Collaboration

• Work alongside product managers, data scientists, and backend engineers to integrate AI capabilities into application ecosystems.
• Conduct experiments to evaluate new AI tools, frameworks, and model architecture updates

Skills & Qualifications Required

• AI & LLM Stack: Strong proficiency in Python, SQL, and GenAI frameworks (LangChain, LangGraph, CrewAI, AutoGen).
• Agentic Design: Hands-on experience building agents with tool-calling capabilities, memory retention, guardrails, and structured outputs.
• Retrieval & Data: Solid understanding of RAG architectures, embedding models, prompt engineering, and vector databases (e.g., Pinecone, Qdrant, Chroma, Weaviate).
• API & Integration: Experience building REST APIs (e.g., FastAPI) and moving data across external APIs and SQL databases.
• Cloud & DevOps: Practical experience with Docker, container management, and cloud infrastructure (AWS, Azure, or GCP).

Preferred

• 3+ years of focused experience building and shipping LLM applications or agents in production settings.
• Familiarity with AI observability and evaluation tools (e.g., LangSmith, Phoenix, MLflow).
• Demonstrable portfolio, open-source contributions, or GitHub projects focused on AI agent development.

Skills Required: GenAI, LLM, Agentic AI, RAG Cloud Platforms

Important :

Notice period : Immediate to 15-30 days ONLY.

Candidates serving Notice period will be preferred.

Please note - There should not be Career Gap more than 6 months(No Career Break)

Graduation score should be 60% & above

Pre Screening BGV (Background Verification)is mandatory [UAN/PF without any overlap issue is required.]