Infra AI Automation Lead

Key Responsibilities:

• •As an Infra AI Automation Lead you will take ownership of building and delivering AI automation solutions while guiding a team of engineers
• •You will be expected to stay hands on designing developing and deploying AI systems using Python deep learning and generative models while also taking responsibility for the team s technical direction code quality and delivery outcomes
• •Beyond execution you will work closely with architects and business stakeholders to ensure what is built is aligned to real needs and built to last
• •Client Engagement and Needs Analysis
• •Lead client meetings and workshops to understand business objectives and identify Gen AI use cases
• •Assess client technology infrastructure data landscape and AI maturity to recommend adoption approaches
• •Translate business requirements into clear technical problem statements for internal teams
• •Gen AI Strategy and Solution Design
• •Design and deliver end to end Gen AI solutions LLM applications RAG pipelines fine tuned models and agentic workflows
• •Define Agentic AI architectures using frameworks such as LangChain LlamaIndex CrewAI AutoGen or Semantic Kernel
• •Recommend appropriate platforms tools and APIs based on client needs and develop implementation roadmaps with clear milestones
• •Ensure solutions are scalable and integrate effectively with existing enterprise systems ERP CRM Data Lakes
• •MLOps LLMOps and Model Lifecycle
• •Establish MLOps LLMOps practices CI CD model versioning observability and cost optimization
• •Oversee end to end model lifecycle from training through deployment and monitoring
• •Implement guardrails feedback loops and perform statistical analysis to drive continuous improvement
• •Technical Guidance and Implementation Support
• •Provide technical guidance to AI ML engineers and review code model configurations and solution designs
• •Mentor junior engineers through design reviews pairing and structured feedback
• •Collaborate with architects to break down high level designs into actionable engineering tasks
• •Drive data preparation fine tuning workflows validation strategies and model evaluation pipelines

Technical Requirements:

• •At least 5 years of programming experience in Python
• •Hands on experience delivering end to end Gen AI solutions
• •Strong experience with LLMs OpenAI Azure OpenAI Hugging Face Anthropic etc

• •Hands on experience with TensorFlow PyTorch LangChain LlamaIndex and Prompt Engineering
• •Experience building Agentic AI systems and multi agent frameworks LangGraph CrewAI AutoGen Semantic Kernel etc

• •Experience with vector databases FAISS Pinecone Weaviate Chroma and RAG pipelines
• •Working knowledge of MLOps LLMOps practices CI CD model versioning monitoring and deployment
• •Familiarity with cloud platforms Azure AWS GCP and containerization Docker Kubernetes
• •Experience mentoring or technically guiding junior engineers
• •Good knowledge of deep learning advanced NLP data structures SQL NoSQL
• •Understanding of responsible AI and ethical AI frameworks
• •Strong communication analytical and problem solving skills

Additional Responsibilities:

• •Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile
• •These include
• •High analytical skills
• •A high degree of initiative and flexibility
• •High customer orientation
• •High quality awareness
• •Excellent verbal and written communication skills

Preferred Skills:

• Technology->AI-Agentic AI->AgentOps,Technology->AI-AI Engineering->MLOps,Technology->AI-Generative AI->Generative AI - Basic,Technology->AI-Traditional AI->TensorFlow,Technology->OpenSystem->Python - OpenSystem->Python
• Experience: 0.00-0.00 Years