Role & responsibilities

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 engineering (vLLM, SGLang etc.)
- Guardrails and AI governance
- GPU deployment and model serving
- AI observability and telemetry

Engineering Skills

- Python ecosystem
- LangChain/LangGraph/CrewAI ecosystems
- Cloud-native AI deployment
- Distributed inference systems
- AI workflow orchestration

Preferred Experience

- 5+ to 12+ years in AI/ML engineering
- Hands-on GenAI platform engineering experience
- Experience with enterprise AI governance
- Exposure to regulated industry AI deployment

Location: Bangalore, Chennai

📌 Gen AI Engineer/Lead/Architect (Tamil Nadu)
🏢 Momento Cybertech Solutions
📍 Tamil Nadu