What are the responsibilities and job description for the Machine Learning Engineer position at Xaxis Solutions?
We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, build, and deploy next-generation AI solutions. In this role, you will work at the intersection of LLMs, autonomous agents, retrieval-augmented generation (RAG), and enterprise-scale systems, leveraging Azure AI Foundry, Copilot Studio, and modern orchestration frameworks.
You will collaborate closely with product managers, architects, and application teams to deliver intelligent, production-grade AI agents that integrate seamlessly with business workflows and enterprise data.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
5 years of experience in machine learning, AI engineering, or applied ML
Strong proficiency in Python for ML and backend development
Hands-on experience building LLM-based applications
Practical experience with agentic AI patterns (tool calling, planning, memory, reflection)
Experience with LangChain or similar agent orchestration frameworks
Solid understanding of RAG architectures
Experience with vector databases (e.g., Azure AI Search, Pinecone, etc.)
Familiarity with Azure cloud services and enterprise-grade deployments
Hands-on experience with MCP and/or A2A agent communication frameworks
Key Responsibilities
Design and implement agentic AI systems capable of planning, tool use, memory, and multi-step reasoning
Build and deploy AI solutions using Azure AI Foundry and Copilot Studio
Develop RAG pipelines integrating structured and unstructured enterprise data
Implement and optimize vector databases for semantic search and long-term agent memory
Orchestrate LLM-based agents using frameworks such as LangChain (or equivalent)
Develop scalable backend services and APIs using Python
Integrate AI agents with enterprise tools, APIs, and workflows
Evaluate, monitor, and optimize agent performance, reliability, and cost
Apply responsible AI principles including security, privacy, and governance
Stay current with advancements in LLMs, agent architectures, and Azure AI services
Preferred Qualifications
Direct experience with Azure AI Foundry and Copilot Studio
Experience integrating AI agents into enterprise workflows or SaaS platforms
Knowledge of prompt engineering, evaluation frameworks, and guardrails
Experience with CI/CD, MLOps, or AI observability
Understanding of security, identity, and compliance in enterprise AI systems
Nice-to-Have
Contributions to AI prototypes, internal platforms, or open-source projects
Experience moving AI solutions from prototype to production
Strong communication skills and ability to explain complex AI systems to non-experts