AI Architect

AI Architect OpportunityAs an AI architect, you will play a crucial role in designing and implementing end-to-end full-stack solutions for Agentic AI applications.Key Responsibilities:Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments.Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration.Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.Requirements:Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.Advanced proficiency in Python programming.Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex, or similar AI frameworks.Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.Tools and Technologies:Programming Languages & Frameworks: Python, FastAPI, FlaskAI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndexDatabases: Neo4j, Vector DatabasesCloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCPContainerization & Orchestration: Docker, KubernetesInfrastructure as Code: TerraformData Processing & Pipelines: Snowflake SQL, AWS-native servicesDevOps & CI/CD: CI/CD pipelines, observability toolsOther: Knowledge of AI governance, ethical AI