Monstro · 7 hours ago
Senior AI Engineer
NYC or Denver Metro
Full-time
Hybrid
Senior Level
$189K/yr - $235K/yr
7+ years expMonstro is an AI-native fintech platform reimagining how people and institutions manage money. They are seeking a Senior AI Engineer who will build AI-powered capabilities, design and implement autonomous AI systems, and ensure the quality and safety of AI outputs while collaborating with junior engineers and product managers.
AccountingEdTechFinanceFinTechInsurTechLegal TechPersonal FinanceWealth Management
Responsibilities
Write clean, maintainable, well-tested code
Design APIs, services, and data models with the same rigor expected of any senior engineer
Participate in code reviews, contribute to architecture decisions, and uphold engineering best practices across the codebase
Own features end-to-end—from design through deployment and monitoring
Design and implement autonomous AI agents with planning, memory, and tool-use capabilities
Build orchestration layers that coordinate multi-step agent workflows, manage conversational context, and handle fallback behaviors gracefully
Integrate both commercial model APIs and self-hosted open-weight models depending on the requirements of each use case
Deploy and manage self-hosted open-weight LLMs within secure cloud environments
Optimize inference performance through quantization, batching strategies, and efficient serving frameworks (vLLM, TGI, or similar)
Integrate commercial model APIs (Anthropic, OpenAI, etc.) where appropriate, managing cost, latency, and reliability
Build systems that can operate in environments with limited or no external network access
Design retrieval-augmented generation pipelines that ground AI responses in authoritative, up-to-date information
Develop chunking, indexing, and retrieval strategies optimized for financial content
Integrate AI systems with structured knowledge bases and real-time data sources
Develop evaluation frameworks that measure reliability, consistency, and safety—not just accuracy
Build automated testing pipelines for AI systems, including regression testing, adversarial testing, and edge case detection
Implement guardrails that prevent harmful, biased, or off-topic outputs
Design transparency mechanisms and audit trails that support compliance and debugging
Adapt open-weight foundation models for domain-specific tasks using techniques like instruction tuning, LoRA, QLoRA, and parameter-efficient fine-tuning
Implement prompt engineering strategies and evaluate their effectiveness
Optimize model performance for latency, cost, and quality tradeoffs
Implement monitoring for model drift, latency, error rates, and output quality
Design for graceful degradation when models or services underperform
Create feedback loops that surface production issues and drive continuous improvement
Collaborate with Data Engineers and ML Engineers to ensure seamless integration with data pipelines and feature stores
Mentor junior engineers on AI development and software engineering best practices
Collaborate with product managers and domain experts to translate business needs into AI capabilities
Communicate complex AI concepts clearly to technical and non-technical stakeholders
Qualification
Required
7+ years of software engineering experience, with a track record of shipping production systems
Strong proficiency in Python and/or Go, with clean, well-structured code
Solid understanding of software engineering fundamentals: system design, API design, testing, code review, CI/CD, and version control
Experience with containerization (Docker, Kubernetes) and cloud infrastructure
Comfort owning features end-to-end, from design through deployment and observability
3+ years of hands-on experience building AI/ML-powered features or products
Experience building agentic AI systems—chat interfaces, multi-step workflows, tool-use patterns, and orchestration frameworks (LangChain, LangGraph, or similar)
Working experience with both commercial LLM APIs (Anthropic, OpenAI) and open-weight models (LLaMA, Mistral, Qwen, or similar)
Experience designing and implementing RAG pipelines with vector databases
Strong understanding of prompt engineering and LLM behavior optimization
Familiarity with model serving frameworks (vLLM, TGI, Triton, or similar) and inference optimization techniques
Experience with model adaptation techniques (LoRA, QLoRA, PEFT, instruction tuning)
Experience building evaluation and testing frameworks for AI systems
A problem solver at heart—you dig into complex problems, explore options, and find practical solutions rather than waiting for direction
Proactive and self-driven; you identify opportunities and risks before they become blockers
Innovative and curious; you keep up with a fast-moving field and bring new ideas to the team
Passionate about building AI systems that are both powerful and trustworthy
Excellent communicator who can explain AI behavior and limitations clearly to any audience
Benefits
Paid health, vision, dental, and disability coverage
Company
Monstro
Your independent guide to building and protecting your wealth.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase