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.
Primary Skill: Artificial Intelligence/Machine Learni
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
ards