Agentic AI Engineer

Job Summary

We are seeking a highly skilled Agentic AI Engineer / Applied AI Engineer to design, develop, and deploy next-generation AI systems that leverage Large Language Models (LLMs), autonomous agents, retrieval systems, and intelligent workflows to solve complex enterprise problems. The ideal candidate combines strong software engineering fundamentals with applied AI/ML experience and thrives in fast-paced, innovation-driven environments.

Key Responsibilities

AI & Agentic Systems Development

• Design and implement intelligent AI agents capable of reasoning, planning, tool usage, memory management, and multi-step workflow execution.

• Build production-grade LLM applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar orchestration platforms.

• Develop Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise knowledge systems.

• Create autonomous workflows that integrate APIs, tools, databases, and enterprise services.

Applied AI Engineering

• Fine-tune, evaluate, and optimize LLMs and generative AI systems for enterprise use cases.

• Develop prompt engineering strategies, evaluation pipelines, guardrails, and AI safety mechanisms.

• Implement AI observability, monitoring, hallucination detection, and performance optimization solutions.

• Work with structured and unstructured data pipelines for AI model consumption.

Software Engineering & Platform Development

• Build scalable backend services and APIs using Python, Java, Node.js, or Go.

• Design cloud-native AI architectures on platforms such as AWS, Azure, or GCP.

• Develop microservices and containerized applications using Docker and Kubernetes.

• Implement CI/CD pipelines, testing frameworks, and infrastructure-as-code practices.

Leadership & Collaboration

• Lead technical design discussions and architecture reviews.

• Mentor junior engineers and provide guidance on AI engineering best practices.

• Collaborate with product managers, data scientists, architects, and business stakeholders.

• Drive technical innovation and contribute to enterprise AI strategy.