We are seeking a highly skilled Automation AI Developer with 56 years of experience in building scalable automation solutions, backend systems, data pipelines, and Generative AI applications. The ideal candidate will have strong expertise in Python development, API integrations, databases, ETL processes, and modern AI technologies such as Large Language Models (LLMs), RAG, AI Agents, and Vector Databases.

The role involves designing and developing intelligent automation solutions, AI-powered applications, and enterprise-grade data workflows that drive operational efficiency and business insights. The candidate will work closely with solution architects, data engineers, and business stakeholders to deliver scalable, secure, and innovative AI-driven products and automation platforms.

Key Responsibilities

Design, develop, and maintain scalable automation solutions, backend applications, and AI-powered systems.
Build and manage RESTful APIs using Python frameworks such as FastAPI.
Develop and optimize data pipelines, ETL processes, and data integration workflows.
Design and implement Generative AI applications, including AI assistants, chatbots, copilots, and intelligent automation solutions.
Develop and integrate Retrieval-Augmented Generation (RAG) frameworks, vector databases, and semantic search capabilities.
Build AI Agent workflows using Tool Calling, Function Calling, and orchestration frameworks such as LangChain, LangGraph, or similar technologies.
Integrate enterprise systems, third-party applications, and cloud services through APIs and automation frameworks.
Design and manage relational, NoSQL, and vector database solutions to support AI and analytics applications.
Implement caching mechanisms and performance optimization strategies using Redis or similar technologies.
Perform data processing, analysis, and visualization using Python libraries such as Pandas, NumPy, and Plotly.
Collaborate with Solution Architects, Data Engineers, Frontend Developers, and Business Stakeholders to deliver end-to-end AI and automation solutions.
Ensure application scalability, security, reliability, and adherence to software engineering best practices.
Conduct code reviews, testing, troubleshooting, and performance tuning to maintain high-quality deliverables.
Stay current with emerging technologies in Generative AI, Agentic AI, Machine Learning, and cloud platforms, and recommend innovative solutions for business challenges.
Contribute to technical documentation, architecture discussions, and continuous improvement initiatives.
Strong hands-on experience with Python development.
Advanced knowledge of SQL and database design principles.
Experience developing and consuming REST APIs using FastAPI.
Experience working with Redis or similar caching technologies.
Hands-on experience with Vector Databases such as Pinecone, Chroma, Weaviate, or Milvus.
Strong proficiency in Pandas, NumPy, Plotly, and related Python libraries.
Basic understanding of Machine Learning concepts and associated libraries.
Experience building or supporting Generative AI applications.
Hands-on experience with Large Language Models (LLMs) such as GPT, Claude, Gemini, or open-source models.
Experience implementing Retrieval-Augmented Generation (RAG) architectures.
Experience with Tool Calling, Function Calling, and AI Agent workflows.
Experience using AI frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
Knowledge of Prompt Engineering, context management, and AI application development best practices.
Understanding of vector embeddings, semantic search, and knowledge retrieval systems.
Knowledge of software engineering best practices, version control, and CI/CD pipelines.
Experience with Model Context Protocol (MCP).
Experience with ETL development and orchestration tools such as Apache Airflow.
Familiarity with Agentic AI frameworks such as CrewAI, AutoGen, or similar.
Experience developing conversational AI applications, AI assistants, or copilots.
Knowledge of AI observability and monitoring tools such as LangSmith, Phoenix, or Weights & Biases.
Familiarity with AI and cloud-native services on AWS, Azure, or GCP (Azure OpenAI, AWS Bedrock, Vertex AI).
Exposure to Docker, Kubernetes, and cloud deployment practices.
Understanding of MLOps, model deployment, and AI governance concepts.

Required Skills

Good to Have

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
56 years of experience in AI Development, Automation Engineering, Data Engineering, or AI Application Development.
Experience delivering enterprise-scale automation, analytics, or AI transformation projects.

Strong analytical, problem-solving, and communication skills

Associate Process Manager