Artificial Intelligence Engineer

About Intellectyx Intellectyx.ai is an AI-native innovation company that empowers enterprises to transition from conventional digital systems to autonomous, agentic, and data-intelligent ecosystems . We specialize in combining data observability , AI orchestration , and contextual intelligence to help organizations operate faster, smarter, and with greater trust. Role Overview As an AI Engineer , you will play a key role in designing, building, and deploying agentic AI systems and intelligent data pipelines across Intellectyx’s product suite and enterprise clients. You will work at the intersection of LLMs, data engineering, and cloud architecture , developing adaptive AI workflows that integrate seamlessly into digital and data platforms. This role requires a blend of strong software engineering, data science, and system integration skills — ideal for someone who thrives in building next-generation AI-native solutions that are explainable, scalable, and autonomous. Key Responsibilities 1. AI Development & Integration Develop and operationalize LLM- and agent-based systems using AgnoAI , MCP , LangChain , LangGraph , and Langfuse . Implement reasoning chains, memory modules, and contextual orchestration for autonomous agents. Integrate AI pipelines into existing FastAPI / Django applications and PostgreSQL / Snowflake data backends. 2. Data Engineering & Processing Build and optimize data ingestion and transformation pipelines using Databricks , Azure Data Factory , and Snowflake . Enable real-time data availability for AI agents and models through semantic and vector-based retrieval. Collaborate with data scientists to train, deploy, and monitor ML/LLM models at scale. 3. Agentic Architecture Implementation Contribute to multi-agent frameworks that enable autonomous workflows across digital, data, and business processes. Implement AI governance mechanisms , including prompt management, context versioning, and safe execution boundaries. Build APIs for inter-agent communication, feedback loops, and observability tracking. 4. Cloud & DevOps Deploy AI services in AWS and Azure environments using containerized and serverless approaches. Implement observability tools for monitoring agent performance, cost, and latency. Work with DevOps teams on CI/CD pipelines , MLOps , and model lifecycle management. 5. Visualization & Decision Support Collaborate with teams using Tableau and Power BI to operationalize AI-driven insights for business consumption. Enable human-in-the-loop workflows and dashboards for monitoring AI behavior and data quality. Qualifications 3–7 years of experience in AI, ML, or software engineering roles. Strong programming background in Python (FastAPI, Django, LangChain ecosystem). Hands-on experience with: Agentic AI: AgnoAI, MCP, LangChain, LangGraph, Langfuse, OpenAI APIs, vector databases Data: Snowflake, Databricks, Azure Synapse, Azure Data Factory Cloud: AWS, Azure, Terraform, Docker, Kubernetes Visualization: Tableau, Power BI Proficiency with LLMs , prompt engineering , and embedding-based retrieval (e.g., FAISS, pgvector). Experience with model evaluation, observability, and performance optimization. Familiarity with Git , CI/CD pipelines , and API-based system design . Preferred Experience Prior experience in building agent-based or multi-agent orchestration systems . Exposure to LangGraph or AgnoAI orchestration pipelines for agent collaboration. Contributions to open-source AI or MLOps projects. Soft Skills Excellent problem-solving, critical thinking, and analytical skills. Strong communication and collaboration abilities within cross-functional teams. Curiosity-driven mindset with a passion for experimentation and learning. Why Intellectyx Be part of an AI-native engineering culture that’s pioneering agentic intelligence for enterprise ecosystems. Work on global-scale projects integrating Digital, Data, AI, and Cloud architectures. Competitive compensation, global exposure, and opportunities to lead innovation initiatives.