Skip to main content

Senior Backend AI Engineer

Posted today

neshent technologiesElizabethport (NJ)

SENIORITY

Lead

Apply (opens in a new tab)

About the role

Role 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.

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.

More like this