Title - Lead Software Engineer Full Stack & Agentic AI

Location: Charlotte, NC (Day 1 Onsite)

Experience 10 + Years

Position Summary:

We are seeking a highly skilled and innovative Lead Software Engineer to drive the design, development, and delivery of next-generation intelligent applications powered by Agentic AI. This role combines deep expertise in full-stack software engineering with hands-on experience building AI-powered systems, autonomous agents, Retrieval-Augmented Generation (RAG) architectures, and enterprise-scale AI solutions.

As a technical leader, you will define architecture, establish engineering standards, mentor development teams, and guide the implementation of AI-driven solutions that deliver measurable business value. You will work across the entire software development lifecycle, from requirements analysis and architecture design through implementation, deployment, and production support.

The ideal candidate possesses strong software engineering fundamentals, extensive experience with modern web technologies, and a proven track record designing and implementing Agentic AI platforms, intelligent workflows, and AI-enabled business solutions.

Key Responsibilities

Technical Leadership

  • Lead architecture, design, and development of enterprise-grade applications and AI-enabled platforms.
  • Serve as the technical lead for complex modernization, automation, and digital transformation initiatives.
  • Drive engineering best practices, code quality standards, security requirements, and architectural governance.
  • Mentor and coach software engineers, promoting technical excellence and continuous learning.
  • Conduct design reviews, architecture reviews, and critical code reviews.

Full Stack Development

  • Design and develop scalable backend services using Java Spring Boot and Python.
  • Build modern, responsive web applications using Angular and React.
  • Develop and maintain RESTful APIs, microservices, and event-driven architectures.
  • Integrate applications with cloud services, external APIs, and enterprise systems.
  • Design and optimize relational database solutions using SQL Server and Oracle.

Agentic AI Solution Development

  • Design and implement Agentic AI architectures capable of reasoning, planning, tool usage, memory management, and autonomous execution.
  • Build intelligent agents leveraging Large Language Models (LLMs), multi-agent orchestration, and AI workflow automation.
  • Develop Retrieval-Augmented Generation (RAG) solutions utilizing vector databases, semantic search, embeddings, and knowledge repositories.
  • Create prompt engineering frameworks, reusable prompt libraries, and evaluation methodologies.
  • Design AI evaluation, monitoring, observability, and feedback mechanisms to ensure solution quality and reliability.
  • Collaborate with business stakeholders to identify AI opportunities and translate them into production-ready solutions.
  • Implement responsible AI practices, including guardrails, security controls, and human-in-the-loop workflows.

Data and AI Engineering

  • Design and implement semantic data repositories, knowledge graphs, and business metadata frameworks.
  • Develop AI-powered solutions that leverage structured and unstructured enterprise data.
  • Optimize AI retrieval pipelines for performance, scalability, and accuracy.
  • Support data quality, lineage, governance, and metadata management initiatives.
  • Build scalable vector search solutions and AI-powered knowledge management platforms.

DevOps & Platform Engineering

  • Design and support CI/CD pipelines and automated deployment strategies.
  • Implement testing frameworks, including unit, integration, performance, and AI evaluation testing.
  • Partner with platform and infrastructure teams to deploy scalable cloud-native applications.
  • Monitor production systems and establish operational excellence practices.

Required Qualifications

Experience

  • 8+ years of professional software engineering experience.
  • 3+ years leading technical teams or serving as a lead engineer.
  • 2+ years designing and implementing Generative AI or Agentic AI solutions in enterprise environments.
  • Demonstrated experience delivering large-scale enterprise applications from inception through production.

Technical Skills

Programming Languages

  • Advanced Python development
  • Advanced Java (Spring Boot)
  • Strong SQL development

Front-End Technologies

  • Advanced Angular
  • Advanced React
  • TypeScript
  • HTML5, CSS3, JavaScript

Databases

  • SQL Server
  • Oracle Database
  • Experience with database design, performance tuning, and optimization

AI & Machine Learning

  • Large Language Models (LLMs)
  • Agentic AI architecture and implementation
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • Vector Databases (e.g., Pinecone, Weaviate, Chroma, Milvus, Azure AI Search)
  • Embedding models
  • Semantic search
  • AI evaluation frameworks
  • Multi-agent orchestration

Cloud & DevOps

  • Azure, AWS, or Google Cloud
  • Docker
  • Kubernetes
  • GitHub Actions / CI-CD pipelines
  • Infrastructure as Code

Architecture

  • Microservices architecture
  • Event-driven architecture
  • API design and integration
  • Distributed systems
  • Domain-driven design

Preferred Qualifications

  • Experience building enterprise AI platforms and AI governance frameworks.
  • Experience with Microsoft Copilot Studio, Azure AI Foundry, LangChain, LangGraph, or similar agent frameworks.
  • Experience designing knowledge graphs and semantic data models.
  • Experience implementing AI observability, evaluation, and monitoring solutions.
  • Experience with modernization and legacy transformation initiatives.
  • Experience with GitHub Copilot, AI-assisted software development, and automated code generation workflows.
  • Exposure to machine learning operations (MLOps) and AI Operations (AIOps).

Leadership Competencies

  • Strong strategic and systems-thinking mindset.
  • Ability to translate business challenges into scalable technical solutions.
  • Excellent communication and stakeholder management skills.
  • Proven ability to influence architecture and engineering decisions across teams.
  • Strong mentoring and coaching capabilities.
  • Passion for innovation, emerging technologies, and AI-enabled transformation.

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