Role Summary:

The role will own the AI and GenAI architecture, including LLM lifecycle management, agentic orchestration, prompt engineering, model optimization, inference engineering, guardrails and evaluation frameworks.

The individual will lead the implementation of enterprise-grade AI-assisted rule transformation and governance capabilities.

Should be able to lead a team of engineers, excellent skill in hands on coding and extremely proficient in doing effective code review for production grade code.

Key Responsibilities:

AI Platform Architecture
Design agentic orchestration frameworks
Implement AI-assisted rule transformation pipelines
Drive LLM integration and optimization strategy

LLM Engineering
Build enterprise-ready LLM libraries
Fine-tune and optimize foundation models
Design configuration-based choices to use either proprietary LLM models or local hosted models from LLM libraries
Design prompt engineering and orchestration frameworks
Implement inference optimization strategies

NLP & Rule Intelligence




Implement sentence extraction and semantic parsing pipelines
Support AST normalization and canonical transformation
Build semantic comparison and amendment intelligence
Support RAG and vector retrieval frameworks

Governance & AI Safety
Implement AI guardrails and safety controls
Define evaluation and benchmarking frameworks
Support explainability and AI observability
Implement policy-aware execution boundaries

Runtime & Optimization
Implement scalable inference architecture
Optimize latency, throughput and deployment efficiency
Support GPU orchestration and inference engineering
Drive model lifecycle governance

Required Skills

AI & LLM Skills
LLM fine-tuning, pretraining and model optimization
Agentic architecture and orchestration
Advanced prompt engineering
NLP and semantic extraction
Evaluation and benchmarking frameworks

AI Platform Skills
RAG and vector database architecture
Inference eng

📌 Ai/ml Engineer Veerapur (India)
🏢 Momento Cybertech Solutions
📍 India