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Artificial Intelligence Engineer

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Hybrid

Artificial Intelligence Engineer

Pi Square Technologies

Artificial Intelligence Engineer

Skills

Google Cloud PlatformSQL QueriesDockerReactPythonAIAWSGitHubKubernetesFastAPIAzure

20 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

30 September 2026

What they need


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.]

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