Systems Integration Advisor

AI Architect

PAN India Immediate to 30 Days

• Design, develop, and deploy scalable software solutions leveraging modern architectures and cloud platforms.
• Build and implement Agentic AI systems (LLM-based autonomous agents, multi-agent frameworks, orchestration workflows) to automate complex business processes.
• Hands-on experience with
  
  GenAI (LLMs, RAG, embeddings, prompt engineering).
• Experience with traditional ML(classification, regression, NLP, time-series).
• Develop and maintain data engineering pipelines (ETL/ELT) for structured and unstructured data across enterprise systems.
• Integrate AI models (LLMs, NLP, GenAI) into applications using tools such as Azure OpenAI,Lang Chain, Semantic Kernel, or similar frameworks.
• Architect data platforms supportingreal-time and batch processing using technologies like Spark, Databricks, or cloud-native services.
• Collaborate with cross-functional teams to deliver client demos, POCs, and production-ready solutions.
• Ensure data quality, governance, and security across all data workflows.
• Optimize system performance, reliability, and scalability across AI and data components.

• Strong experience in software development (Python6+ yrs).
• Hands-on experience with Agentic AI / autonomous agents, including:
  
  Multi-agent orchestration
  
  Tool usage & reasoning workflows
  
  Prompt engineering and memory management2+years experience with
  
  GenAI (LLMs, RAG, embeddings, prompt engineering)
  Solid background in data engineering, including:
  
  Data pipelines, ETL/ELT processes
  
  Data modeling and warehousing
  
  Streaming and batch processing
  
  Experience with cloud platforms (Azure preferred) and services like:
  
  Azure Data Factory / Synapse / Databricks Azure OpenAI / Cognitive Services Familiarity with vector databases, embeddings, and RAG architectures.
• Strong understanding of API design, microservices, and distributed systems.

• Degree:
  
  Bachelor'sin computer science/IT or equivalent program (4 yrs).
• Experience with
  
  GenAI frameworks (Lang Chain,Llama Index, Semantic Kernel).
• Exposure to MLOps/LLMOpspractices.
• Experience building enterprise-grade AI copilots or automation solutions.
• Knowledge of data governance and observability frameworks.

• Ability tooperatein a fast-paced, client-facing environment.
• Strong problem-solving and ownership mindset.
• Capability toanticipateproject needs, especially during client demos and critical delivery windows.