VP AI/ML Software Engineer - LLM Engineer / GenAI Engineer - Fulltime
PURVIEW
Weehawken, NJ (In Person)
$175,000 Salary, Full-Time
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Job Description
VP AI/ML
Software Engineer- LLM Engineer / GenAI Engineer
- Fulltime at
PURVIEW VP AI/ML
Software Engineer- LLM Engineer / GenAI Engineer
- Fulltime at PURVIEW in Weehawken, New Jersey Posted in about 5 hours ago.
Type:
full-timeJob Description:
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 + Bonus We are seeking a hands-on Senior AI Engineer to design, build, and deploy production-grade agentic AI systems at scale.
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 solutions
Required 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 environments
MUST-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 stakeholders Not 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 coding This 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.
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