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