Senior GenAI Cloud Engineer

Senior GenAI Cloud Engineer

Location: Newark, NJ Hybrid preferred but open to Remote candidates for the right fit

Duration: 6 Months

ABOUT THE ROLE

We are seeking a Senior GenAI Cloud Engineer to build and deploy enterprise-scale AI solutions that drive intelligent automation, conversational experiences, and business process transformation.

This is a hands-on engineering role responsible for designing, developing, and delivering production-grade AI applications using modern cloud architectures, large language models, and agentic AI frameworks. You will lead the implementation of specific workstreams end-to-end, mentor less experienced engineers, and contribute to the architecture and standards used by many engineering teams. The ideal candidate has recent experience building AI agents, chatbots, and RAG-based solutions in enterprise environments.

KEY RESPONSIBILITIES

• Develop cloud-native applications and microservices using Python and JavaScript/TypeScript.
• Build and deploy enterprise AI agents, chatbots, and GenAI-powered applications.
• Implement data ingestion, document processing, embedding generation, vectorization, and retrieval pipelines.
• Develop intent classification, orchestration, guardrail, and safety capabilities for AI applications.
• Integrate LLMs with enterprise systems, APIs, databases, and business workflows.
• Contribute to system design, testing, deployment, monitoring, and operational support.
• Uphold code quality, security, and observability standards in everything you ship.
• Stay current with emerging AI technologies, frameworks, and platform capabilities.

LEADERSHIP, MENTORING & INFLUENCE

• Lead a workstream: Take technical ownership of a defined feature area or service - from design through production support - coordinating a small group of engineers where needed.
• Mentor engineers: Guide associate and mid-level engineers through code review, pairing, and design feedback; help them build GenAI and cloud skills.
• Contribute to architecture: Participate actively in design reviews, propose solution options with clear trade-offs, and help shape the patterns and standards the team adopts.
• Influence through delivery: Partner directly with product owners, architects, and business stakeholders to refine requirements and build credibility through working software.
• Improve the team: Identify and drive improvements in engineering practices, tooling, reusable components, and documentation; share knowledge through demos and internal write-ups.

REQUIRED QUALIFICATIONS

• 5–8 years of software engineering experience.
• Strong proficiency in Python and JavaScript/TypeScript.
• Experience developing microservices, APIs, and distributed applications.
• Hands-on experience with AWS cloud services and cloud-native application development.
• Recent experience building enterprise GenAI solutions, including AI agents, chatbots, or RAG applications.
• Experience with AWS Bedrock or other enterprise LLM platforms.
• Experience with data ingestion, vector databases, embeddings, and semantic search.
• Experience implementing AI guardrails, safety controls, intent classification, and routing logic.
• Strong understanding of software engineering best practices, application security, scalability, and production operations.
• Experience mentoring engineers and leading delivery of a technical workstream.

PREFERRED QUALIFICATIONS

• Experience with AWS AgentCore.
• Experience with LangGraph, LangChain, or similar agent frameworks.
• Experience with model tuning, evaluation, and prompt engineering.
• Experience with event-driven architectures and AWS serverless technologies.
• Experience delivering solutions in financial services, insurance, or other regulated industries.

IDEAL CANDIDATE

You are a strong software engineer with recent GenAI experience who enjoys building production-ready AI solutions. You have hands-on experience developing agents, chatbots, and retrieval-based applications, you are comfortable across cloud architecture, application development, and AI integration challenges; and you naturally raise the level of the engineers around you.

LEVELING: SENIOR VS. LEAD

• Senior GenAI Cloud Engineer - 5–8 years. Primarily hands-on. Leads implementation of specific workstreams, contributes to architecture, mentors associate and mid-level engineers, and influences within the team.
• Lead GenAI Cloud Engineer - 8 years. Hands-on technical leader. Owns architecture and technical direction, sets standards and platform strategy, leads complex multi-team initiatives, mentors senior engineers, and influences cross-team design decisions.
• Career path: GenAI Cloud Engineer → Senior GenAI Cloud Engineer → Lead GenAI Cloud Engineer.