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
