Mode of Interview

Internal Virtual

Internal – In-person

Client Round – Virtual

Job Description:

AI Engineer – GenAI & Multi-Agent Systems.

Role Overview

We are looking for a highly skilled AI Engineer specializing in Generative AI and Multi-Agent Systems to design and deploy intelligent, autonomous solutions.

This role focuses on building LLM-powered, agent-driven architectures that can reason, collaborate, and execute complex workflows across enterprise systems.

You will work on cutting-edge Agentic AI frameworks, enabling systems that go beyond prediction to decision-making, orchestration, and autonomous execution.

Key Responsibilities

* Design and build multi-agent AI systems capable of planning, reasoning, and task execution

* Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestration

* Implement Agentic workflows (planner executor critic memory loops)

* Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge grounding

* Develop tool-using agents that integrate with APIs, databases, and enterprise systems

* Architect and deploy AI copilots and autonomous assistants for business workflows

* Optimize LLM performance using fine-tuning, prompt chaining, and caching strategies

* Implement short-term and long-term memory mechanisms (vector stores, knowledge graphs)

* Design multi-agent collaboration protocols (hierarchical, swarm, role-based agents)

* Deploy scalable solutions using MLOps + LLMOps practices (monitoring, evaluation, guardrails)

* Ensure AI safety, governance, and responsible AI practices

Required Skills & Qualifications

* Bachelor’s/Master’s in Computer Science, AI, or related field

* 3–8 years experience in AI/ML with strong focus on Generative AI

* Solid Python development skills

* Hands-on experience with:

- LLMs & GenAI frameworks: OpenAI,



Hugging Face Transformers
- Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kernel
- RAG pipelines & vector DBs: FAISS, Pinecone, Weaviate

* Experience building API-driven, tool-integrated AI agents

* Strong understanding of:

- Prompt engineering & prompt optimization
- Chain-of-thought reasoning and tool augmentation
- Context management and token optimization

* Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptable)

* Knowledge of Docker, Kubernetes, CI/CD pipelines

Preferred Qualifications

* Experience building multi-agent orchestration systems with role-based coordination

* Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree-of-Thought)

* Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfoo)

* Knowledge of graph-based reasoning / knowledge graphs

* Building autonomous systems or copilots in enterprise environments

* Domain experience in industrial, energy, or IoT environments

Key Competencies

* Systems thinking for designing autonomous AI architectures

* Strong problem decomposition for agent task design

* Ability to balance latency, cost, and accuracy in LLM systems

* Communication with business stakeholders to translate workflows into agent pipelines

* Innovation mindset with focus on applying agentic AI in production

Tech Stack (Modern GenAI Stack)

* Languages: Python

* Frameworks: LangChain, CrewAI, AutoGen, Semantic Kernel

* LLMs: OpenAI GPT, Azure OpenAI, Claude, Llama

* Vector DB: Pinecone, Weaviate, FAISS

* Orchestration: Airflow, Prefect

* Deployment: Docker, Kubernetes

* Cloud: Azure AI Studio / Azure ML (preferred)

KPIs / Success Metrics

* Autonomous task completion rate of agents

* Reduction in manual workflows via AI automation

* Latency and cost optimization of LLM pipelines

* Accuracy and reliability of agent outputs

* Adoption rate of AI copilots across teams

📌 Artificial Intelligence Engineer (Karnataka)
🏢 Hardwin Software Solutions
📍 Karnataka