Description

Job Description

Key Responsibilities :

Solution Architecture

Design and oversee secure, scalable enterprise AI/ML and Generative AI (LLM/SLM) architectures.
Define solution architecture for AI-powered applications and enterprise workflows.
Design architectures covering RAG, LLMs, agentic AI, intelligent automation, and AI assistants.
Ensure solutions meet requirements around security, scalability, reliability, performance, and cost.

AI Strategy & Governance

Define AI reference architectures, technology roadmaps, and engineering standards.
Establish AI governance frameworks covering Responsible AI, model deployment, security, and compliance.
Evaluate emerging AI technologies and identify opportunities for enterprise adoption.

GenAI & Technology Integration

Architect and implement use cases such as :
Intelligent chatbots
Automated document processing
RAG applications
Agentic workflows
Enterprise AI assistants
Work with LLMs, SLMs, vector databases, embeddings, and semantic search.
Integrate modern GenAI orchestration frameworks into enterprise solutions.

Technical Leadership

Establish and contribute to AI Centers of Excellence (CoE).
Mentor and guide AI Engineers, ML Engineers, Data Scientists, Architects, and MLOps teams.
Conduct architecture and technical design reviews.
Define best practices for AI engineering, deployment, monitoring, and optimization.

Consulting & Pre-Sales

Lead AI discovery and solutioning workshops with customers.
Support RFP/RFI responses and technical solution proposals.
Develop AI transformation roadmaps aligned with business objectives.
Present AI architecture and transformation strategies to senior stakeholders.

Mandatory Skills

AI / ML :

Machine Learning & Deep Learning
Generative AI / LLMs / SLMs
RAG
AI/ML Solution Architecture
TensorFlow / PyTorch

GenAI Frameworks

LangChain
LangGraph
Semantic Kernel
Agentic AI

Cloud & MLOps

Azure and/or AWS
Cloud-native AI services
Docker / Kubernetes
CI/CD pipelines
MLOps / LLMOps
Model deployment and monitoring

Good To Have

Vector databases
Knowledge Graphs
Semantic Search
Prompt Engineering
LLM Evaluation
Responsible AI & AI Governance
Azure OpenAI / Amazon Bedrock
Enterprise AI security
Experience building reusable AI accelerators and frameworks

Preferred Candidate Profile

5 - 10 years of overall IT experience with significant hands-on AI/ML architecture experience.
Proven experience designing and delivering enterprise-scale AI/GenAI solutions.
Strong understanding of cloud architecture and MLOps.
Experience leading technical teams and mentoring AI/ML professionals.
Strong consulting, communication, stakeholder-management, and presentation skills.
Ability to translate business requirements into scalable AI solutions

Key Skills

Education

Any Graduate