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 Google Cloud Platform. 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.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or related field. 5+ years of software engineering experience. 2+ years of hands-on experience building Generative AI or LLM-based applications. 1+ Claude MCP integrations. Strong programming skills in Python and at least one additional language (Java, Go, JavaScript/TypeScript). Experience with LLM APIs such as OpenAI, Anthropic, or open-source models. Experience with vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB. Experience with RAG architectures and semantic search. Experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform. Strong understanding of software design patterns, system scalability, and observability.

Preferred Qualifications

Experience with multi-agent orchestration systems. Familiarity with AI governance, responsible AI, and enterprise security standards. Experience deploying AI systems in healthcare, retail, insurance, or pharmacy domains. Knowledge of reinforcement learning, model fine-tuning, or evaluation frameworks. Contributions to open-source AI projects or published technical research.

Nice-to-Have

Experience Healthcare or pharmacy technology experience. Experience building conversational AI platforms or enterprise copilots. Knowledge of HIPAA, compliance, and regulated AI environments. Exposure to graph-based orchestration and workflow engines.