Artificial Intelligence Engineer

We are seeking a highly skilled AI Engineer with a Master’s degree in Computer Science, Artificial Intelligence, or a related field to design, develop, and deploy advanced AI/ML systems. This role is centered on building next-generation agentic AI solutions powered by retrieval-augmented generation (RAG), leveraging modern orchestration frameworks such as LangGraph and Model Context Protocol (MCP).

The ideal candidate will have deep expertise in Python-based AI development and hands-on experience designing agent systems capable of reasoning, planning, tool usage, and executing complex multi-step workflows. A strong foundation in end-to-end RAG architectures, including Graph RAG, is required.

ng Secondary Skill: Pyth

on Tertiary Skill: Natural Language Processi

n

g Required Qualificatio

• nsMaster’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related fiel
• d.Strong proficiency in Python programming, with experience building scalable AI/ML system
• s.Hands-on experience with agentic AI frameworks, particularly LangGraph, and emerging standards such as Model Context Protocol (MCP
• ).Strong experience designing and implementing advanced RAG architectures, including Graph RA
• G.Experience with LLM orchestration frameworks such as LangChain, LangGraph, and LlamaInde
• x.Proven experience deploying LLM-powered production system
• s.Design and implement advanced RAG pipelines using vector databases, embeddings, knowledge graphs, and hybrid retrieval strategie
• s.Develop agentic AI systems using LangGraph, enabling dynamic task planning, reasoning, tool orchestration, and multi-agent workflow
• s.Integrate Model Context Protocol (MCP) for standardized context sharing, tool interoperability, and scalable agent communicatio
• n.Design memory systems and contextual state management for agent continuity and long-running workflow
• s.Implement evaluation pipelines, prompt engineering strategies, and guardrails to ensure performance, safety, and reliabilit
• y.Apply Model Risk Management (MRM) practices across the AI lifecycle, including model validation, explainability, bias detection, monitoring, and documentatio
• n.Strong experience with Python ML/AI frameworks such as PyTorch, TensorFlow, and Scikit-lear
• n.Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search) and semantic retrieval system
• s.Deep understanding of agent orchestration patterns, including planning, reflection, tool usage, and multi-agent collaboratio
• n.Experience implementing Graph RAG using knowledge graphs and structured data integratio
• n.Expertise in memory architectures (short-term, long-term, episodic memory) in agent system
• s.Strong understanding of LLMOps/MLOps, including CI/CD, observability, monitoring, and performance optimizatio
• n.Working knowledge of Model Risk Management (MRM) frameworks including governance, validation, and lifecycle control
• s.Familiarity with AI safety and alignment techniques, including guardrails, human-in-the-loop systems, and bias mitigatio
• n.Experience with model evaluation, benchmarking, and explainability tools
• .Proficiency with development tools such as GitHub, VS Code, JIRA, and modern engineering workflow

s.
Desired Qualificati

• onsExperience working in an Agile development methodology; experience with RAG and

LLM
Intake No

• tes:Overview of the work being
• doneDesign and develop production-grade Python APIs/serv
• icesDeploy and operate applications on OpenS
• hiftPartner with AI/ML engineers to productionize model capabilities into usable backend serv
• icesRemediate vulnerabilities
• in:Python libraries/dependen
• ciesContainer im
• agesOpenShift deployment configurat
• ionsPrimarily internal collaboration with cross-functional teams such as AI/ML engineers, UI developers, DevOps, and security/compliance stakehold
• ers.Building Python-based microservices/APIs that expose AI/ML model functionality to downstream applicat
• ionsDeploying containerized applications to OpenShift and configuring manifests, services, routes, and sec
• retsIntegrating backend APIs with Angular-based front-end applicat
• ionsPerforming remediation of security findings in Python dependencies and container im
• agesAutomating deployment workflows using CI/CD pipelines aligned with OpenShift stand