VP AI/ML Software Engineer – LLM Engineer / GenAI Engineer - Fulltime

Hiring: Senior AI Engineer – Agentic AI & LLM Systems (Backend + Architecture)Locations: Jersey City, NJ | Dallas, TX | Menlo Park, CA | Seattle, WA (Onsite)Full-Time$150K – $200K Base + BonusWe are seeking a hands-on Senior AI Engineer to design, build, and deploy production-grade agentic AI systems at scale. This role requires a strong combination of backend engineering, LLM system design, and architectural thinking.This is an individual contributor role for engineers who can not only build systems but also clearly articulate high-level design, tradeoffs, and production considerations.What You’ll Do:• Design and implement end-to-end AI systems, including ingestion, retrieval, orchestration, and evaluation layers• Build and deploy multi-agent AI systems (planning, reasoning, tool usage, coordination)• Develop scalable backend services and APIs for AI-driven applications• Architect RAG pipelines and hybrid retrieval systems for enterprise use cases• Define and implement LLMOps practices, including evaluation frameworks, monitoring, and observability• Optimize systems for latency, scalability, cost, and reliability• Integrate AI systems with cloud infrastructure, distributed systems, and enterprise platforms• Collaborate with cross-functional teams to translate business needs into scalable AI solutionsRequired Qualifications:• 8–15 years of experience in software engineering, AI/ML engineering, or platform engineering• Strong programming skills in Python (required)• Proven experience building production-grade distributed systems and APIs• Hands-on experience with LLMs and GenAI systems in production environmentsMUST-HAVE SKILLS:• Experience designing and building multi-agent AI systems (LangGraph, CrewAI, AutoGen, MCP, or similar)• Strong understanding of LLM system architecture, including orchestration, memory, retrieval, and tool usage• Experience with RAG pipelines, vector databases, and hybrid retrieval strategies• Experience implementing LLM evaluation frameworks (LLM-as-judge, hallucination detection, benchmarking)• Strong knowledge of cloud platforms (AWS preferred) and distributed systems (Kubernetes, Docker)• Experience with event-driven architectures (Kafka, streaming pipelines, async processing)Preferred Qualifications:• Experience building enterprise-scale AI platforms• Familiarity with observability tools (Prometheus, Grafana, OpenTelemetry)• Exposure to financial services or regulated environments• Experience explaining system design and tradeoffs to both technical and non-technical stakeholdersNot a Fit If:• You are primarily a data scientist or research-focused ML engineer• Limited experience with production system design and deployment• Experience is limited to POCs, demos, or basic chatbot/RAG implementations• Primarily focused on people management or high-level strategy without hands-on codingThis role is ideal for engineers who can design, build, and explain production AI systems end-to-end — combining deep technical execution with strong system-level thinking.