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