Overview

We are looking for an experienced AI Software Engineer to build and deliver production-grade Agentic AI solutions across enterprise applications. The ideal candidate will have strong software engineering fundamentals with hands-on experience developing AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, APIs, cloud-native services, and modern application frameworks.

This role requires a highly adaptable engineer capable of working across multiple programming languages and technology stacks while translating business processes into scalable AI-enabled solutions.

Key Responsibilities

AI Solution Development

• Design, develop, and deploy production-ready Agentic AI applications.
  
• Build intelligent AI agents with:
  
  • Tool integrations
    
  • Retrieval-Augmented Generation (RAG)
    
  • Context management
    
  • Memory
    
  • Stateful conversations
    
  • Human approvals
    
  • Exception handling
    
• Deliver enterprise AI assistants and AI-enabled applications.
  

Application Development

• Build scalable backend services using:
  
  • FastAPI
    
  • Spring Boot
    
  • Node.js
    
• Develop responsive frontend applications using:
  
  • React.js
    
• Design reusable application components and shared services.
  

API & Service Engineering

• Develop secure RESTful APIs and microservices.
  
• Build event-driven services and asynchronous workflows.
  
• Design integrations between AI services, enterprise systems, and business applications.
  
• Develop data transformation pipelines and service orchestration.
  

AI Platform Engineering

• Build production-grade RAG pipelines.
  
• Integrate Large Language Models (LLMs) into enterprise applications.
  
• Implement AI tracing, monitoring, and observability.
  
• Develop scalable AI services with robust context handling and orchestration.
  

Software Engineering

• Translate business processes into:
  
  • User stories
    
  • Technical designs
    
  • APIs
    
  • Interfaces
    
  • Acceptance criteria
    
  • Test scenarios
    
• Build maintainable, scalable, and secure enterprise software.
  
• Write comprehensive unit, integration, and end-to-end tests.
  

DevOps & Deployment

• Deploy AI applications using enterprise CI/CD pipelines.
  
• Containerize applications using Docker and Kubernetes.
  
• Support production deployments and post-production monitoring.
  
• Ensure application reliability, scalability, and performance.
  

Required Skills & Experience

• 7+ years of experience in Software Engineering, Platform Engineering, AI/ML Engineering, or Application Development.
  
• Proven experience delivering production AI applications.
  
• Hands-on experience with:
  
  • Large Language Models (LLMs)
    
  • Retrieval-Augmented Generation (RAG)
    
  • AI Assistants
    
  • Agentic AI
    
• Strong backend engineering experience.
  
• Experience building enterprise APIs and distributed systems.
  
• Strong knowledge of containerization and CI/CD practices.
  
• Production ownership of AI-enabled applications.
  

Primary Skills

Programming Languages

• Python
  
• Java
  
• TypeScript
  

Backend Development

• FastAPI
  
• Spring Boot
  
• Node.js
  

Frontend

• React.js
  

AI & Machine Learning

• Agentic AI
  
• Large Language Models (LLMs)
  
• Retrieval-Augmented Generation (RAG)
  
• AI Assistants
  
• Context Management
  
• Prompt Engineering
  

AI Frameworks

• MCP (Model Context Protocol)
  

Databases

• SQL
  
• NoSQL Databases
  

Cloud & Containers

• Kubernetes
  
• Docker
  
• REST APIs
  

DevOps

• CI/CD Pipelines
  
• Git
  
• Automated Deployments
  

Observability

• AI Tracing
  
• Application Monitoring
  
• Logging
  
• Performance Monitoring
  

Secondary Skills (Good to Have)

• LangChain
  
• LangGraph
  
• CrewAI
  
• AutoGen
  
• Semantic Kernel
  
• Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
  
• OpenTelemetry
  
• Event-Driven Architecture
  
• Microservices
  
• Graph Databases
  
• Prompt Optimization
  
• MLOps
  
• Cloud Platforms (Azure, AWS, GCP)
  
• API Gateway
  
• Distributed Systems
  
• AI Security & Governance
  

Required Skills & Experience

• 7+ years of experience in Software Engineering, Platform Engineering, AI/ML Engineering, or Application Development.
  
• Proven experience delivering production AI applications.
  
• Hands-on experience with:
  
  • Large Language Models (LLMs)
    
  • Retrieval-Augmented Generation (RAG)
    
  • AI Assistants
    
  • Agentic AI
    
• Strong backend engineering experience.
  
• Experience building enterprise APIs and distributed systems.
  
• Strong knowledge of containerization and CI/CD practices.
  
• Production ownership of AI-enabled applications.
  

Primary Skills

Programming Languages

• Python
  
• Java
  
• TypeScript
  

Backend Development

• FastAPI
  
• Spring Boot
  
• Node.js
  

Frontend

• React.js
  

AI & Machine Learning

• Agentic AI
  
• Large Language Models (LLMs)
  
• Retrieval-Augmented Generation (RAG)
  
• AI Assistants
  
• Context Management
  
• Prompt Engineering
  

AI Frameworks

• MCP (Model Context Protocol)
  

Databases

• SQL
  
• NoSQL Databases
  

Cloud & Containers

• Kubernetes
  
• Docker
  
• REST APIs
  

DevOps

• CI/CD Pipelines
  
• Git
  
• Automated Deployments
  

Observability

• AI Tracing
  
• Application Monitoring
  
• Logging
  
• Performance Monitoring
  

Secondary Skills (Good to Have)

• LangChain
  
• LangGraph
  
• CrewAI
  
• AutoGen
  
• Semantic Kernel
  
• Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
  
• OpenTelemetry
  
• Event-Driven Architecture
  
• Microservices
  
• Graph Databases
  
• Prompt Optimization
  
• MLOps
  
• Cloud Platforms (Azure, AWS, GCP)
  
• API Gateway
  
• Distributed Systems
  
• AI Security & Governance
  

Diversity Inclusion:

At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career.

Exavalu also promotes flexibility  depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also have a welcome back program to help people get back to the mainstream after a long break due to health or family reasons.