AI Agent Developer

Unlock the future of intelligent automation with a visionary AI Developer who excels in crafting agentic AI applications that effortlessly connect with structured databases. If you're passionate about pushing technological boundaries, possess deep expertise in LLMs, RAG, and orchestration frameworks, and thrive on transforming complex business needs into scalable, AI-driven solutions, this is your opportunity to make a transformative impact.

Key Responsibilities:

• Design and develop agentic bots powered by Large Language Models (LLMs) to interact with structured databases (SQL, Snowflake, etc.).
• Integrate AI agents with external tools and data sources using Model Context Protocol (MCP).
• Implement RAG pipelines using vector databases (e.g., Pinecone, FAISS, Weaviate, ChromaDB) to enable accurate information retrieval.
• Build and optimize conversational workflows leveraging frameworks such as LangChain, LlamaIndex, or similar orchestration tools.
• Develop natural language-to-SQL mapping systems that allow users to query structured databases via conversational interfaces.
• Collaborate with data engineers, data scientists, and business stakeholders to define requirements, integrate datasets, and deliver impactful AI use cases.
• Deploy, monitor, and optimize AI applications in production using MLOps practices (CI/CD, containerization, model versioning).
• Ensure AI systems comply with data security, privacy, and governance standards.
• Stay current with emerging AI/ML tools, frameworks, and best practices, proactively bringing innovation into solutions.

Qualifications:

• Bachelors or Masters in Computer Science, AI/ML, Data Science, or a related field with a minimum of 1+ years in AI/ML development.
• Strong programming skills in Python with hands-on experience building APIs and backend services.
• Hands-on experience with Model Context Protocol (MCP) to extend AI agents capabilities with external tools and context.
• Experience with LLMs and GenAI APIs (OpenAI, Anthropic, Hugging Face, Azure OpenAI), and AI orchestration frameworks (LangChain, LlamaIndex, or equivalent).
• Experience integrating AI applications with structured databases (Snowflake, Postgres, MySQL) and working with SQL.
• Familiarity with vector databases and embedding models for semantic search and RAG.

Preferred Skills:

• Knowledge of MLOps practices (CI/CD, Docker, Kubernetes, MLflow).
• Experience deploying AI apps on AWS (SageMaker, Lambda, S3) or other cloud platforms.
• Knowledge of Power BI or Tableau for integrating AI outputs into business intelligence dashboards.
• Prior experience building chatbots, virtual assistants, or intelligent automation solutions.