Senior Backend Ai Engineer

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., * 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., Rafferty is hiring two hands-on Lead AI Engineers as founding members of its AI Center of Excellence. This is a forward-deployed role. You will work inside business operations with Rafferty’s in-house IT lead and the people who run the work every day. You will find where AI helps in operations, compliance, risk management, and client service, then build the tools, put them into daily use, and keep improving them.

This is initially a senior individual contributor role with no direct reports. You own each solution end to end, from discovery to production support, and coordinate the input, decisions, and approvals of the right stakeholders.

What success looks like

• Production AI tools in daily use by the business teams you sit with, with measurable outcomes defined up front and tracked after launch.
• Solutions delivered in line with the firm’s AI strategy and technology roadmap.
• AI engineering, prompt engineering, and governance standards that teams use.
• Reusable AI components, prompt libraries, and agent frameworks that make each new use case faster to build.
• A pipeline of high-value use cases found inside business workflows.
• The foundation of a scalable, sustainable AI Center of Excellence., * Work directly with operations, compliance, risk, and client service teams. Sit with the operators, learn how they do the work today, and find where AI removes friction.
• Take each use case from discovery and scoping through build, deployment, adoption, and ongoing support.
• Turn what you observe into clear problem statements, then into working software inside the systems people already use.
• Put early versions in front of the people who will use them, watch how they work, and refine quickly based on their feedback.
• Design, develop, deploy, and support enterprise AI applications and services.
• Build solutions with LLMs, RAG architectures, AI agents, machine learning models, and intelligent automation.
• Design, test, and optimize prompts to improve accuracy, consistency, reliability, and business outcomes.
• Develop reusable prompt libraries, workflows, and AI solution frameworks.
• Build APIs, integrations, and cloud-native services that speed AI adoption across the firm.
• Set standards and best practices for AI architecture, prompt engineering, model evaluation, testing, and deployment.
• Implement monitoring, governance, and controls for secure and responsible AI use.
• Work with business, technology, compliance, risk, and security teams, and with the in-house IT lead, to deliver AI solutions that fit the firm’s environment.
• Before launch, document the production support model: ownership of monitoring, incidents, enhancements, controls, and solution retirement.
• Evaluate emerging AI technologies and recommend where to adopt them.
• Mentor future AI team members and help grow the AI Center of Excellence.

• 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., * 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., * 5+ years of software engineering experience delivering enterprise applications and technology solutions.
• 3+ years developing and deploying AI or machine learning solutions in production.
• A track record of working directly with business users to scope problems and ship tools they adopt, in a forward-deployed, solutions engineering, or embedded engineering role, or equivalent.
• Hands-on experience with LLMs, prompt engineering, RAG, AI agents and workflow orchestration, vector databases and semantic search, and model evaluation and testing frameworks.
• Experience building on enterprise AI platforms such as Azure OpenAI, Anthropic Claude, OpenAI, or equivalent.
• Proven experience designing, testing, and optimizing prompts for enterprise AI applications.
• Strong understanding of context engineering, structured outputs, grounding, retrieval optimization, and prompt evaluation methods.
• Strong Python skills and experience building APIs, microservices, and cloud-native applications.
• Experience with Microsoft Azure, AWS, or Google Cloud.
• Familiarity with DevOps, CI/CD, MLOps, and AI governance practices.
• Strong analytical, communication, and stakeholder management skills, including explaining technical trade-offs to non-technical colleagues.
• Experience working in regulated environments with security, compliance, and governance requirements., * Financial services experience in asset management, wealth management, banking, capital markets, brokerage, insurance, or fintech.
• Experience with Azure OpenAI Service, Anthropic Claude, Azure AI Foundry, Microsoft Copilot Studio, Microsoft Fabric, Databricks, LangChain, LangGraph, or Semantic Kernel.
• Experience building enterprise AI assistants, copilots, agentic AI solutions, or multi-agent systems.
• Experience establishing AI governance and responsible AI frameworks.
• Knowledge of investment operations, client servicing, compliance, risk management, or financial products.
• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related field.

Hiring salary range: $225,000 to $250,000, plus bonus.

Benefits: medical, dental, vision, 401(k) plan, life insurance, and unlimited PTO. #J-18808-Ljbffr

Black Osprey is hiring on behalf of our client, Rafferty Holdings. This is a full-time role at Rafferty Holdings, based in the Long Island office in Garden City, NY, working on-site or hybrid. A second opening is based in New York City.