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Fornax
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AI Engineer

AI Engineer

Fornax

1 years

0 Lacs

India

Posted:1 day ago| Platform:

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Skills Required

ai data automate analyze strategy consulting analytics engineering architecture development design automation orchestration content service marketing optimization communication messaging management coordination logic escalation efficiency integration openai model tuning evaluation monitoring devops logging auto scaling deployment security compliance ml software

Work Mode

On-site

Job Type

Full Time

Job Description

Company Description

Fornax is a data-driven solutions company dedicated to helping clients optimize, automate, and analyze their data. Our mission is to transform raw data into valuable insights for faster, more accurate decision-making. We specialize in data strategy consulting, data analytics, data engineering, and robust data infrastructure. With a focus on scalable and customized solutions, we empower businesses of all sizes to unlock their data's true potential.

Key Responsibilities :

AI System Architecture & Development ( 40% ) :

Design and implement intelligent automation systems and agentic AI architectures using advanced orchestration patterns
Develop specialized AI systems for specific business functions (content generation, customer service, marketing optimization, analytics)
Build communication frameworks with event-driven messaging and shared context management for agentic workflows
Implement coordination logic for complex, multi-step business processes with autonomous decision-making
Create robust error handling, fallback mechanisms, and escalation protocols for agentic systems
Optimize system performance for cost efficiency and response time

LLM Integration & Optimisation ( 30 % ) :

Integrate multiple LLM providers (OpenAI, Anthropic, open-source models) with intelligent routing
Design and maintain prompt engineering frameworks with dynamic template systems
Implement model selection logic based on task complexity, cost, and performance requirements
Build fine-tuning pipelines for domain-specific model optimization
Create evaluation frameworks for AI system performance and output quality
Manage token usage optimization and cost monitoring across all systems

Infrastructure & DevOps ( 10%) :

Deploy and maintain AI systems in cloud environments (AWS)
Implement monitoring, logging, and alerting for system operations
Design auto-scaling infrastructure for variable AI workloads
Manage deployment pipelines and version control for system updates
Ensure system security, data privacy, and compliance requirements
Optimize infrastructure costs and resource utilization

Key Qualifications

Education

Experience

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