The Agentic AI Engineer is a hands-on development role specializing in building and deploying production AI agent solutions for clients.

In this client-facing consulting position, you will work in a hybrid environment delivering cutting edge AI agents that blend large language models, custom prompts, data sources, and business logic across financial, manufacturing, and enterprise domains.

AI Agent Development: Code core logic for AI agents (standalone or multi-agent systems) to answer questions, generate content, or execute automated transactions.

GenAI & RAG Engineering: Build and optimize Retrieval-Augmented Generation (RAG) systems, implementing vector indices, embedding models, prompt orchestration, and fallback strategies for grounded outputs. System Integration: Interface AI agents with external systems, databases, and microservices using RESTful APIs and event-driven architectures.

Deployment & MLOps: Package and deploy agent applications using containerization (Docker) and cloud platforms, ensuring scalability, continuous integration, logging, and performance monitoring. Ethics & Guardrails: Implement content moderation, data privacy, and governance alignment adhering to responsible AI guidelines.

CORE TECHNICAL STACK & SKILLS:

Programming & APIs Python (primary), FastAPI, Flask, RESTful APIs, JSON/XML data formats, PyTest

AI/ML & Agent Frameworks LLM APIs (OpenAI, Azure OpenAI), LangChain, PyTorch/TensorFlow, Vector Databases (Pinecone, Weaviate), NLP

Infrastructure & MLOps Docker, Git, Cloud Platforms (AWS, Azure, GCP), Event Streams (Kafka, RabbitMQ, SQS), Monitoring (CloudWatch, Application Insights