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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack & Agentic AI - **Company:** Saransh Inc - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Salary:** $116,000.0 - $174,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, HTML5, Microsoft Azure, Cascading Style Sheets (CSS), Code Generation, Software Quality, Code Review, Databases, Continuous Integration, Data Stores, Relational Databases, Database Design, DevOps, Distributed Systems, Memory Management, Github, Graph Database, Python (Programming Language), Knowledge Management, Meta-Data Management, Microsoft SQL Server, Oracle Databases, Oracle (Applications), Performance Tuning, Cloud Services, Search Technologies, Software Engineering, TypeScript, Google Cloud, Enterprise Software Applications, Microsoft Power Automate, Spring Cloud, GitHub Copilot, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Generative AI, Backend, Event Driven Architecture, AI Platforms, AngularJS, Kubernetes, Deployment Automation, Web Technologies, Machine Learning Operations, Front End Software Development, Virtual Agents, Api Design, Restful APIs, Domain Driven Design, Docker, Web Api, Programming Languages, Microservices - **Published:** August 1, 2026 - **Apply:** https://www.careerjet.com/jobad/usbfd2a856e5700a3bd84ce3756459c376 ## About the Role * 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, * 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. ## Description 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., 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. ## Related Videos - [The AI-Native Engineering Org: What’s Real, What’s Hype, What’s Next](https://www.wearedevelopers.com/videos/100004-the-ai-native-engineering-org-what-s-real-what-s-hype-what-s-next) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [The Resilience of the World Wide Web](https://www.wearedevelopers.com/videos/1281-the-resilience-of-the-world-wide-web) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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