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Vivanet
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AI Engineer

AI Engineer

Vivanet

6 years

0 Lacs

pune maharashtra india

Posted:7 hours ago| Platform:

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Skills Required

ai technology leadership power research design reasoning model engineering software planning management collaboration retrieval data debugging optimization communication aws gcp azure docker deployment automation

Work Mode

On-site

Job Type

Full Time

Job Description

AI Engineer

Experience:

Location:

Employment Type:

About Vivanet

Vivanet

harnessing the power of Agentic AI

AI Engineer

About the Role

AI Engineer at Vivanet

AI engineering, software design, and problem solving

Key Responsibilities

Design and develop
Agentic AI systems
capable of reasoning, planning, and executing complex tasks autonomously.
Build and optimize AI pipelines using
LangChain
,
LangGraph
, and related frameworks for context management, memory, and orchestration.
Work with
MCP (Model Context Protocol)
to establish structured context sharing and inter-agent communication.
Integrate AI components into scalable APIs and backend systems for enterprise deployment.
Collaborate with product and engineering teams to design
end-to-end intelligent workflows
aligned with business objectives.
Evaluate and integrate new frameworks, models, and tools to enhance solution performance and adaptability.

Required Skills

Strong proficiency in
Python
and hands-on experience with AI frameworks like
LangChain
,
LangGraph
,
LlamaIndex
,
PyTorch
,
Transformers
, or
FastAPI
.
Working knowledge of
Agentic AI architectures
, including multi-agent collaboration, reasoning, and tool-use systems.
Familiarity with
MCP (Model Context Protocol)
and structured context handling.
Experience in
RAG (Retrieval-Augmented Generation)
pipelines and
vector databases
(Pinecone, FAISS, Milvus).
Solid grounding in
data structures, algorithms
, and
software design principles
.
Strong debugging, performance optimization, and communication skills.

Desired / Nice-to-Have

Experience with
Java
, especially for backend or microservice integration.
Exposure to
knowledge graphs
,
function calling
, and
multi-agent orchestration
.
Familiarity with
cloud platforms
(AWS, GCP, Azure) and
containerization
(Docker, Kubernetes).
Understanding of
DevOps
– CI/CD for models, deployment automation, and monitoring.

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