Technical Specialist

Technical Expert – Agentic AI & Enterprise Platforms Key Responsibilities

• Architect and develop enterprise-grade Agentic AI
  , Generative AI
  , and Machine Learning solutions.
• Design and implement intelligent workflows, multi-agent systems, and AI orchestration frameworks.
• Build and optimize custom machine learning models for classification, prediction, segmentation, recommendation, and analytics use cases.
• Lead development of RAG (Retrieval-Augmented Generation), semantic search, and knowledge retrieval solutions.
• Design scalable data pipelines leveraging Snowflake, Databricks, and cloud-native technologies.
• Develop and deploy AI services, APIs, and microservices for production environments.
• Define architecture standards, coding best practices, governance, security, and performance guidelines.
• Mentor developers, conduct design reviews, and drive technical excellence across teams.
• Evaluate emerging AI technologies and recommend adoption strategies.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 10+ years of experience in software engineering, solution architecture, or platform engineering.
• 5+ years of experience building AI/ML solutions in enterprise environments.
• Strong hands‑on programming experience in Python.
• Proven experience leading architecture and development of large-scale distributed systems.

• Generative AI and Large Language Models (LLMs)
• Agentic AI and Multi-Agent Systems
• RAG Architecture and Semantic Search
• Prompt Engineering
• Fine‑Tuning and Model Evaluation
• Recommendation Systems
• Predictive Analytics
• MLOps and Model Lifecycle Management

• Lang Graph
• Auto Gen
• Lang Chain
• CrewAI (preferred)
• OpenAI APIs
• Anthropic Claude APIs
• Scikit‑Learn
• XGBoost
• Py Torch
• Tensor Flow (preferred)

• Snowflake
• Databricks
• SQL
• Vector Databases
• Data Warehousing Concepts
• Python
• Flask
• REST APIs
• FastAPI (good to have)
• Docker
• Git Hub

• React
• Angular

• Building enterprise AI assistants and conversational platforms.
• Developing AI-powered analytics and decision-support systems.
• Designing agent orchestration frameworks and workflow automation platforms.
• Working with telecom, marketing analytics, customer intelligence, or large-scale enterprise datasets.
• Experience handling datasets with millions of records and deploying AI solutions at scale.
• Exposure to AI governance, responsible AI, and model monitoring frameworks.