VP AI​/ML Software Engineer – Agentic AI & Production Runtime Systems- Fulltime

Title: VP AI/ML Engineer – Agentic AI & Production Runtime Systems

Duration: Full-Time

Salary Range $150K – $200K Base + Bonus

We are looking for a hands‑on AI/ML Engineer to design and build production‑grade agentic AI systems focused on reliability, automation, and large‑scale runtime operations within enterprise environments.

This role combines:

• LLM/GenAI Platform Development
• AI Runtime Automation
• Production Reliability Engineering

The ideal candidate will have deep experience building scalable Python applications, production ML systems, and agentic AI workflows capable of reasoning, orchestrating actions, and integrating with enterprise operational ecosystems.

What You’ll Work On:

• Design and implement multi‑agent AI systems using tool‑calling, retrieval, reasoning, and secure action execution
• Build and product ionize LLM applications using RAG, evaluation frameworks, self‑correction loops, and response validation
• Integrate AI systems with observability, incident management, deployment, and runtime automation platforms
• Develop scalable backend APIs and distributed AI services using Python and cloud‑native architectures
• Build AI reliability, governance, and safety layers including guardrails, policy enforcement, circuit breakers, and rollback mechanisms
• Optimize latency, scalability, and cost through model routing, batching, caching, and context management
• Develop production‑grade monitoring, tracing, telemetry, and evaluation systems for AI services
• Collaborate closely with production engineering and infrastructure teams to automate operational workflows and reduce runtime risk

Required Skills:

• 7+ years of software engineering experience with strong Python development expertise
• Experience building and deploying production ML/AI systems at scale
• Hands‑on experience with:
• Agentic AI systems
• Lang Graph / MCP / tool‑calling workflows
• RAG pipelines and vector retrieval
• LLM evaluation frameworks
• Strong backend engineering and distributed systems experience
• Cloud‑native engineering experience with AWS, Kubernetes, Docker, CI/CD, and observability tooling
• Experience with model serving, inference optimization, and production monitoring

Preferred:

• Experience in financial services, trading systems, or high‑scale enterprise environments
• Experience with OpenAI, Claude, Gemini, Llama, Qwen, or other foundational models
• Strong understanding of reliability engineering, operational automation, and production runtime systems

Not a Fit If:

• Your experience is primarily research‑oriented or academic
• You only have chatbot/POC‑level GenAI experience
• Your background is primarily data science without strong software engineering depth