Senior Backend + AI Engineer

Senior Backend + AI Engineer – Lounge Services

Location: New York, NY

Work Authorization: W2 Only

Work Model: Onsite/Hybrid as required by the client

Job Summary

We are looking for a talented and experienced Senior Backend + AI Engineer to join our growing team. The ideal candidate will have a strong background in backend engineering, distributed systems, cloud technologies, LLM systems, and agentic AI workflows.

The candidate will be responsible for designing and developing scalable backend services while driving the architecture and implementation of production-grade agentic AI systems.

Core Technology Stack

• Languages: Node.js, TypeScript, Go/Golang
• APIs & Services: REST APIs, Microservices
• Cloud & Infrastructure: AWS and/or GCP, Kubernetes, Docker
• Distributed Systems: Event-driven architectures, Kafka
• AI/Orchestration: LangGraph, LangChain, Airflow, and similar frameworks
• Databases: PostgreSQL/SQL, MongoDB, Redis

Responsibilities

• Design, develop, and maintain high-performance, scalable backend services and APIs.
• Collaborate with cross-functional teams to gather requirements, architect solutions, and deliver business-critical features.
• Optimize backend systems for performance, scalability, reliability, and high-volume workloads.
• Drive technical direction for agentic AI initiatives, including architecture patterns, autonomy boundaries, and system design.
• Design, build, deploy, and operate production-grade agentic AI systems across multiple products.
• Own and evolve shared agentic AI capabilities, including:

o Agent frameworks and orchestration layers

o Planning, tool use, and memory strategies

o Retrieval and grounding/RAG pipelines

o LLM infrastructure, inference, and model gateways

o Evaluation, observability, and safety tooling

• Lead technical design reviews and guide teams through trade-offs involving autonomy, safety, reliability, scalability, and cost.
• Establish best practices for code quality, testing, CI/CD, and deployment automation.
• Work closely with DevOps teams to deploy and manage backend services across cloud environments.
• Collaborate with frontend engineers to define API contracts and ensure seamless integration.
• Communicate effectively with engineering teams, stakeholders, and management regarding technical decisions, project status, and recommendations.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field. Master’s degree preferred.
• 10+ years of experience building large-scale distributed systems.
• Strong proficiency in Node.js/JavaScript/TypeScript and/or Golang.
• Strong experience with LLM systems, agentic workflows, or advanced ML infrastructure.
• Proven experience owning complex, cross-cutting agentic AI systems spanning multiple teams or products.
• Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
• Deep understanding of the agentic AI stack, including:

o Planning

o Tool use

o Memory

o RAG/retrieval

o Evaluation

o Observability and safety

• Experience with AI-assisted and agentic software development workflows.
• Ability to operate effectively in ambiguous problem spaces and translate requirements into reliable, production-ready autonomous systems.
• Ability to influence technical direction and align teams without formal authority.
• Experience with workflow engines, asynchronous processing, queues, and streaming systems.
• Hands-on experience with cloud platforms and containerization technologies such as AWS/GCP, Docker, and Kubernetes.
• Strong experience with SQL and NoSQL databases such as PostgreSQL, MongoDB, and Redis.
• Experience with Git and CI/CD pipelines.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Preferred Qualifications

• Experience building agentic AI systems in fintech or other regulated industries.
• Experience as a Founding Engineer, Staff Engineer, Principal Engineer, or early technical leader within an AI-driven product.
• Demonstrated success delivering technically complex autonomous/agentic systems into production.
• Meaningful contributions to open-source AI or agentic frameworks.
• Familiarity with model fine-tuning, optimization, inference pipelines, and LLM infrastructure.