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
- Solid 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

📌 Infra AI Automation Lead (Bengaluru)
🏢 Infosys
📍 Bengaluru