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Home
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Rarr Technologies
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AI Engineer-LLM Integration/Platform Observability

AI Engineer-LLM Integration/Platform Observability

Rarr Technologies

3 - 6 years

5 - 8 Lacs

bengaluru

Posted:1 week ago| Platform:

Apply

Skills Required

computer science performance tuning github orchestration consulting integration testing splunk test cases jira python

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are looking for a

hands-on AI Engineer

with strong expertise in

LLM integration, platform observability, performance optimization, and API development

. The ideal candidate will work on critical platform enhancements, including

LLM API integrations, observability pipelines, structured search algorithms, and performance scaling

for customers AI platform and related components.

You will collaborate with cross-functional teams to develop robust, scalable solutions, modernize our logging and monitoring infrastructure, and integrate advanced AI capabilities into production workflows.

1. LLM Integration & API Development

Develop and maintain
LLM API integration test cases
for core model availability.
Refactor and reorganize
LLM API code (e.g., __init__.py)
for better maintainability.
Add support for
Vertex AI batch generation
and batch transcription processing.
Implement
multi-step structured search algorithms
and tie model IDs to relevant endpoints.
Explore and integrate emerging technologies like
LightRAG, SurrealDB, Neo4j, and Puppygraph
for structured search.

2. Platform Observability & Performance

Implement
Splunk OpenTelemetry (OTel)
integration for monitoring and metrics.
Evaluate and integrate
Arize AI
for observability and model evaluation frameworks.
Optimize
logging decorators
,
memory profiling
for unit tests, and enhance
APM (Application Performance Monitoring)
solutions.
Drive
scaling and performance optimization
for the JedAI platform.

3. Platform Integration & Testing

Implement
platform integration and availability testing frameworks
.
Centralize
Postman test cases
for integration testing.
Clean up
outdated tests
and modernize
Docker Compose setups
for KB API development.
Develop
harness configurations
for automated testing pipelines.

4. Architecture & Research Spikes

Support
JedAI architecture consulting
efforts.
Conduct
spike investigations
on new technologies and frameworks for performance and scalability.
Explore
MCP design
options for multi-agent orchestration and AI-enhanced workflows.

Required Skills & Experience:

Programming:
Python (must-have), Node.js/Java (good to have)
AI/ML Integration:
Hands-on experience with
LLM APIs (OpenAI, Vertex AI, etc.)
Observability & Logging:
Experience with
Splunk, OpenTelemetry (OTel), Arize AI
Testing & CI/CD:
Proficiency with
Postman, Pytest, Docker Compose
Data & Search:
Exposure to
structured search techniques
(Neo4j, LightRAG, Graph DBs)
Performance Tuning:
Familiarity with
memory profiling, performance optimization, and scaling
techniques
Cloud Platforms:
GCP (Vertex AI), Azure, or AWS experience preferred
Collaboration Tools:
GitHub, Jira, Confluence

Preferred Qualifications:

Bachelors or Masters in Computer Science, AI/ML, or related fields
3 6 years of experience in AI/ML engineering or platform development
Prior experience in
AI observability
or
model evaluation pipelines
Knowledge of
Agentic AI frameworks
and
multi-step reasoning systems

Llm Ops, Python

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