Senior AI Engineer

HeartCentrix Solutions; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

HeartCentrix Solutions is seeking a Senior AI Engineer to design production-ready AI agents that connect with enterprise applications and support multiple customer journeys.

You will lead 3–4 engineers, build multi-agent workflows, integrate with Java/Spring Boot microservices via REST APIs, and work with LangGraph, LangChain, and RAG to deliver scalable AI solutions.

Qualifications

• 9+ years of overall experience.
• 5+ years of software development experience.
• 2+ years of hands-on Agentic AI development.
• Strong hands-on experience building AI agents with LangGraph, LangChain, Semantic Kernel, or similar frameworks.
• Strong Python skills.
• Experience with Java and a good understanding of Spring Boot.
• Strong understanding of microservices, distributed systems, REST APIs, and event-driven architecture.
• Experience with prompt engineering, tool/function calling, agent orchestration, and LLM workflows.
• Experience building RAG solutions and working with vector databases.
• Experience integrating AI applications with enterprise systems.

Responsibilities

• Design and build AI agents using LangGraph, LangChain, or similar agent frameworks.
• Build multi-agent workflows, tool integrations, and RAG solutions.
• Connect AI agents with Java/Spring Boot microservices through REST APIs and event-driven architectures.
• Work with prompts, tool/function calling, memory, and agent orchestration.
• Build scalable, reliable AI applications ready for production.
• Help with architecture and technical design decisions.
• Provide technical direction and mentorship to a team of 3–4 engineers.
• Integrate AI solutions with existing enterprise applications and services.
• Work with LLMs such as OpenAI, Claude, Gemini, or similar platforms.

Skills

Python

LangGraph

LangChain

Agentic AI development

Tool/function calling

RAG

REST APIs

Microservices

LLM workflows

Git

Tools

Java

Spring Boot

Docker

Vector databases

Event-driven architectures

Job description

We’re looking for a Senior AI Engineer who can build production-ready AI agents that connect with enterprise applications and support multiple customer journeys on aa.com.

What You’ll Be Doing

• Design and build AI agents using LangGraph, LangChain, or similar agent frameworks.
• Build multi-agent workflows, tool integrations, and RAG solutions.
• Connect AI agents with Java/Spring Boot microservices through REST APIs and event-driven architectures.
• Work with prompts, tool/function calling, memory, and agent orchestration.
• Build scalable, reliable AI applications that are ready for production.
• Help with architecture and technical design decisions.
• Provide technical direction and mentorship to a team of 3–4 engineers.
• Integrate AI solutions with existing enterprise applications and services.
• Work with LLMs such as OpenAI, Claude, Gemini, or similar platforms.

What We’re Looking For

• 9+ years of overall experience.
• 5+ years of software development experience.
• 2+ years of hands‑on Agentic AI development.
• Strong hands‑on experience building AI agents with LangGraph, LangChain, Semantic Kernel, or similar frameworks.
• Strong Python skills — this is a must‑have.
• Experience with Java and a good understanding of Spring Boot.
• Strong understanding of microservices, distributed systems, REST APIs, and event‑driven architecture.
• Experience with prompt engineering, tool/function calling, agent orchestration, and LLM workflows.
• Experience building RAG solutions and working with vector databases.
• Experience integrating AI applications with enterprise systems.

Technical Skills

Required:

• Python
• LangGraph
• LangChain
• Agentic AI development
• Tool/function calling
• RAG
• REST APIs
• Microservices
• LLMs — OpenAI, Claude, Gemini, or similar
• Git

Experience with:

• Java
• Spring Boot
• Docker
• Vector databases such as Pinecone, pgvector, Weaviate, ChromaDB, FAISS, or similar
• Event‑driven architectures

Nice to Have

• MCP (Model Context Protocol) or other AI tool integrations.
• Experience with AI agent evaluation, tracing, and observability.
• Experience building production AI applications at scale.