Senior AI Engineer Agentic Solutions

Job Summary The Senior AI Engineer will design, develop, and deploy AI-native, agentic solutions that transform and modernize business workflows. This role focuses on building production-grade AI systems from the ground up, leveraging large language models (LLMs), agent orchestration frameworks, retrieval-augmented generation (RAG), and enterprise integrations. The ideal candidate will be a hands-on engineer with experience delivering scalable AI solutions in enterprise environments while ensuring compliance with governance, security, and data management standards. Key Responsibilities Design, develop, and deploy end-to-end agentic AI solutions that automate, enhance, or reimagine business workflows. Architect multi-step AI agent pipelines utilizing tool-calling, memory management, retrieval-augmented generation (RAG), and orchestration frameworks. Implement human-in-the-loop workflows and escalation mechanisms for complex or high-risk decision-making processes. Integrate AI systems with enterprise data sources, internal APIs, and third-party platforms while adhering to security and governance requirements. Ensure data quality, model grounding, reliability, observability, and resilient failure handling in production environments. Manage large language model (LLM) integrations, prompt strategies, model selection, and version management. Develop and maintain AI-enabled APIs, data pipelines, and supporting infrastructure. Build and optimize vector database solutions and retrieval systems. Deliver solutions from proof of concept through pilot and production deployment. Collaborate with business stakeholders, process owners, domain experts, and governance teams to develop trusted AI solutions. Monitor, evaluate, and continuously improve deployed AI and agentic systems. Stay current with emerging AI technologies, frameworks, and best practices. Required Qualifications Bachelors degree in a STEM-related discipline. 5+ years of experience in software engineering or a related technical field. 2+ years of experience in AI/ML, LLM-based solutions, and agentic AI system development. Strong proficiency in Python development. Experience developing and integrating REST APIs. Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines. Experience with agent orchestration frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, or similar technologies. Experience deploying, monitoring, and maintaining AI and LLM-based workflows in production environments. Experience developing data pipelines and supporting AI-driven applications. Experience working with vector databases and semantic search solutions. Knowledge of cloud platforms, preferably Microsoft Azure, including Azure AI Foundry and Azure AI Search, or comparable AWS services. Strong problem-solving, analytical, and solution design skills. Ability to work independently and manage projects through full development lifecycles. Excellent communication and collaboration skills. Preferred Qualifications Experience with Databricks in enterprise environments. Experience building enterprise-scale agentic AI platforms and architectures. Experience implementing AI governance, security, and compliance controls. Experience with advanced prompt engineering techniques and model evaluation frameworks. Experience integrating AI solutions with complex enterprise applications and data ecosystems. Experience working with multi-agent architectures and workflow orchestration frameworks. Certifications Relevant cloud, AI, or machine learning certifications related to Microsoft Azure, AWS, or Generative AI technologies Preferred. Education: Bachelors Degree Certification: Artificial Intelligence , AWS , Microsoft Azure , Machine Learning