Senior Backend Ai Engineer

Neshent Technologies; Newark (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Neshent Technologies in Newark, NJ seeks a Senior Backend AI Engineer – Agentic AI to design and scale distributed backends and production‑grade AI solutions.

You will own architecture for autonomous AI systems, build reusable capabilities, and collaborate across teams using Node.js, TypeScript, Golang, and cloud platforms to deliver secure, scalable AI applications.

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• 8+ years of backend engineering experience building scalable, distributed systems.
• Strong proficiency in Node.js, TypeScript, and/or Golang.
• Hands-on experience building and deploying production-grade LLM apps and Agentic AI systems.
• Strong understanding of multi-agent orchestration, planning, tool integration, and memory management.

Responsibilities

• Design, develop, and maintain scalable backend services, APIs, and microservices.
• Architect and build production-grade Agentic AI and multi-agent systems.
• Develop agent orchestration, planning, tool integration, memory, and RAG capabilities.
• Build shared LLM infrastructure, model gateways, evaluation, and observability frameworks.
• Drive architecture decisions across AI initiatives and ensure security and cost efficiency.
• Collaborate with DevOps, frontend, product, and ML teams to deliver end-to-end AI solutions.
• Mentor engineers and influence technical direction.

Skills

Node.js

JavaScript

TypeScript

Golang

REST APIs

Microservices

Distributed Systems

Cloud & DevOps

Kafka

Event-driven Architecture

Airflow

Async Processing

PostgreSQL

MongoDB

Redis

Education

Bachelor's degree in Computer Science, Engineering, or related field

Master's degree preferred

Tools

LangGraph

LangChain

Multi-Agent Systems

Agent Orchestration

Planning

Tool Calling

Memory Management

AWS

GCP

Docker

Kubernetes

CI/CD

Job description

Job Overview

We are looking for a highly experienced Senior Backend AI Engineer – Agentic AI to design, develop, and scale distributed backend systems and production‑grade Agentic AI solutions.

The ideal candidate will have strong expertise in Node.js, TypeScript, and/or Golang, distributed systems, cloud infrastructure, LLMs, and multi‑agent architectures. The role involves driving the technical architecture of autonomous AI systems, building reusable AI capabilities, and delivering scalable, reliable, and secure AI‑powered applications.

Core Technical Skills

• Languages: Node.js, JavaScript, TypeScript, Golang.
• Backend: REST APIs, Microservices, Distributed Systems.
• Agentic AI & LLM: LangGraph, LangChain, Multi‑Agent Systems, Agent Orchestration, Planning, Tool Calling, Memory Management.
• RAG & AI Infrastructure: Retrieval‑Augmented Generation, LLM Integration, Model Gateways, Inference, Evaluation, and Observability.
• Cloud & DevOps: AWS/GCP, Docker, Kubernetes, CI/CD.
• Messaging & Workflows: Kafka, Event‑driven Architecture, Airflow, Async Processing.
• Databases: PostgreSQL, MongoDB, Redis.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field; Master's preferred.
• 8+ years of backend engineering experience building scalable, distributed systems.
• Strong proficiency in Node.js, TypeScript, and/or Golang.
• Hands‑on experience building and deploying production‑grade LLM applications and Agentic AI systems.
• Strong understanding of multi‑agent orchestration, planning, reasoning, tool integration, memory, and RAG.
• Experience with cloud platforms, Kubernetes, microservices, event‑driven architectures, and distributed infrastructure.
• Proven ability to own complex technical initiatives and drive architecture decisions across teams.
• Strong problem‑solving, communication, and technical leadership skills.

Roles & Responsibilities

• Design, develop, and maintain scalable backend services, APIs, and microservices.
• Architect and build production‑grade Agentic AI and multi‑agent systems.
• Develop agent orchestration, planning, tool integration, memory, and RAG capabilities.
• Build and optimize shared LLM infrastructure, model gateways, evaluation, and observability frameworks.
• Drive technical architecture and engineering best practices across AI initiatives.
• Ensure system scalability, reliability, security, performance, and cost efficiency.
• Collaborate with DevOps, frontend, product, and ML teams to deliver end‑to‑end AI solutions.
• Mentor engineers and influence technical direction across teams.

Preferred Qualifications

• Experience building Agentic AI solutions in fintech or regulated industries.
• Experience as a founding engineer or early technical leader in AI‑driven products.
• Contributions to open‑source AI or Agentic AI frameworks.
• Knowledge of model fine‑tuning, optimization, and inference pipelines.
• Experience implementing AI safety, guardrails, and governance mechanisms.

Job Title

AI Engineer – Agentic Development

Duration

6+ Months

Role Type

W2 Role

Generative AI Experience

2+ years

Job Summary

We are seeking highly skilled AI Engineers who can define and scale how engineering teams build simulation software using AI agents.

The ideal candidates should have deep expertise in Agentic AI development and "loop engineering" using tools such as Claude Code. They should be capable of designing feedback loops, guardrails, and workflows that enable AI agents to safely contribute to production codebases.

The role involves the complete agentic software development lifecycle, including context design, evaluation, deployment, and observability, along with hands‑on development across Java, Spring Boot, Node.js, React, Python, and modern frontend technologies.

Key Responsibilities

• Design and implement loop engineering workflows using Claude Code and similar AI tools.
• Define how AI agents plan, execute, test, and iterate on code changes.
• Architect Model Context Protocol (MCP) servers and tool schemas that are safe and easy for LLM agents to use.
• Define human‑in‑the‑loop checkpoints, autonomy boundaries, and rollback strategies for agent‑driven changes.
• Build evaluation harnesses and observability practices to measure agent output quality and catch regressions.
• Design and review microservice and microfrontend architecture using C4 diagrams and Domain‑Driven Design principles.
• Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling.
• Design REST APIs and headless component architectures that support both human developers and AI agents.
• Establish CI/CD practices that safely incorporate agent‑authored pull requests.
• Set and enforce security practices for agentic workflows, including prompt injection risk and tool‑permission boundaries.
• Mentor senior and staff engineers on effective agent‑assisted development.
• Write RFCs and design docs that translate ambiguous problems into actionable technical plans, documents that both humans and agents can act on.

Full Stack Development

• Develop responsive web applications using React.js.
• Build backend services and APIs using Node.js and Express.js.
• Develop backend applications and microservices using Java and Spring Boot.
• Work with React, WebGL.js, and Three.js technologies.
• Integrate AI services and LLM APIs into web applications.
• Design and implement secure RESTful APIs and microservices.
• Develop dashboards for content management, assessment reporting, and learner analytics.

Required Technical Skills

Generative AI & Agentic Development

• Prompt Engineering
• AI Agent Development
• Agentic AI and Multi‑Agent Solutions
• Vector Databases
• LLM Evaluation and Testing
• Tool Integrations
• Claude Code and Loop Engineering
• Node.js
• Express.js
• Java
• Spring Boot
• Python
• REST APIs
• JSON
• Authentication and Authorization

AI Frameworks & Libraries

• LangChain
• LangGraph

Frontend Development

• React.js
• WebGL.js
• Three.js
• HTML5
• CSS3
• Material UI / Bootstrap
• Responsive Design
• Microfrontend Architecture

Databases

• MongoDB
• Redis
• Vector Databases

Preferred Qualifications

• Experience creating technical learning content, hands‑on labs, or certification preparation materials.
• Experience with AI‑based assessment generation and automated evaluation systems.
• Experience building Agentic AI and multi‑agent solutions.
• Experience working with educational technology platforms.
• Experience with simulation software and interactive web technologies.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field.
• 7+ years of overall software development experience.
• 2+ years of Generative AI / LLM application development experience.
• Fundamentals of Machine Learning and AI.
• Basic understanding of LLMs and Generative AI concepts.
• REST APIs and microservices development.
• SQL and data processing.
• Exposure to cloud platforms (Azure/AWS/GCP).
• Knowledge of Git and software development practices.

Preferred

• Exposure to LangChain or OpenAI APIs.
• Understanding of RAG concepts and embeddings.