Staff Applied AI Engineer

FUTURE MODERN; New York (NY); Hybrid; USD 255,000 - 276,000; Full time

Benefits offered by this job

Salary + equity

Health coverage

401(k) match

Flexible time off

Job summary

Future Modern is seeking an Applied AI Engineer to design and ship AI-native product intelligence for a venture-backed B2B SaaS client in NYC. You will build systems that connect user actions with code behind them, with a human in the loop.

You will lead end-to-end MLOps, evaluate models to prevent hallucinations, and collaborate with product and design to frame problems before coding. The role blends full-stack work with core AI development.

Qualifications

• Hands-on experience shipping LLM-powered systems to production.
• Experience with RAG, tool use and agent orchestration.
• Strong model evaluation and hallucination mitigation.
• Understanding of modern model architectures.
• Production MLOps in a live environment.
• Clear communication with engineers, product managers and executives.
• Product judgment: you ask "should we build this?" before "how do we build this?"

Responsibilities

• Design and build applied AI systems from prototype to production.
• Decide prompting vs fine-tuning and explain tradeoffs.
• Build evaluation frameworks and guardrails to limit hallucinations.
• Own end-to-end MLOps: deployment, monitoring, latency, cost, reliability.
• Contribute full-stack when needed.
• Partner with product and design to frame problems before coding.

Skills

LLM systems

RAG pipelines

Agent orchestration

MLOps production

Model evaluation

Cross-functional comms

Product judgment

Tools

LangChain

LlamaIndex

MCP

Custom orchestration

Job description

Future Modern is partnering with a well-established, venture-backed B2B SaaS company that has more than a decade of product usage data across thousands of software teams. They're building a new applied AI team from scratch to ship AI-native product intelligence: systems that connect what users do inside software with the code behind it and recommend improvements, with a human in the loop.

It's not an AI layer bolted onto an existing product. The team moves fast, has high autonomy, and builds things without clear precedents. Applied AI engineers work closely with the company's core software engineers to get products in front of customers.

What you'll do

• Design and build applied AI systems, including RAG pipelines, agentic workflows and LLM-powered features, from prototype through production
• Decide when to prompt, when to fine-tune and when to use a different tool, and explain those tradeoffs to the team
• Build evaluation frameworks, catch hallucinations early, and implement guardrails that hold up under real load
• Own MLOps end to end: deployment, monitoring, latency, cost and reliability
• Contribute full-stack when the product needs it
• Partner with product and design to frame problems before writing code, and push back when the framing is wrong

What you bring

• Deep hands-on experience shipping LLM-powered systems to production, including RAG, tool use and agent orchestration
• Strong command of model evaluation and systematic hallucination mitigation
• Solid understanding of modern model architectures and when to apply them
• Production MLOps experience in a live environment
• Clear communication with engineers, product managers and executives
• Product judgment: you ask "should we build this?" before "how do we build this?"

Nice to have

• Fine-tuning experience and a point of view on when it beats prompting
• Experience with LangChain, LlamaIndex, MCP or custom orchestration
• A background in SaaS or product analytics
• A founding, 0→1 or new-team launch on your resume

Compensation and benefits

• $255,000-$276k base+ equity. Final offer depends on experience.
• Employer-heavy health coverage ($0 premium options), strong 401(k) match, flexible time off

Logistics

• NYC office 3 days a week
• No relocation assistance
• This search is represented by Future Modern. The client is an equal opportunity employer and welcomes people of all backgrounds, experiences, abilities and perspectives.