Senior AI Engineer

от 12 500 $

≈ от 1,1 млн ₽

🌍 УдалённоSeniorПолная занятость🌐 Глобал

от 12 500 $≈ от 1,1 млн ₽

Навык востребован (python).

Нажмите на сигнал, чтобы увидеть, на чём он основан

Наша компания

You’re Opportunity:At PLACE, we’re building a category-defining company at the intersection of real estate, technology, business services, and the consumer. As a profitable, hypergrowth startup on the path to an IPO, our standards are high, our team is scrappy, and our commitment is to execute the best work of our lives. This is YOUR CHANCE to shape the future of AI-powered mortgage technology. As our Director, AI Product, you’ll partner with Product, Engineering, Customer Experience leaders, and executives to define and execute an AI product strategy that transforms how lending teams and borr

О роли

Who Develops You: Head of Product

Чем предстоит заниматься

Design and deliver production AI and agentic systems across document intelligence, workflow automation, and copilots

Own architecture decisions for LLM-based systems, including retrieval, orchestration, memory, tool use, and evaluation

Build and maintain evals and observability frameworks to ensure system quality, reliability, and performance

Optimize systems for cost and latency at production scale

Partner closely with AI Product to scope, sequence, and deliver high-impact features

Collaborate with Data Engineering on pipelines, schemas, and data quality foundations

Mentor engineers working on AI-adjacent systems and elevate team capabilities

Evaluate vendors, models, and tools through POCs, benchmarking, and cost-performance analysis

Ship quickly, iterate in production, and continuously improve system performance

Salary Range: $90,000-150,000/year, depending on experience

Наши требования

6+ years of software engineering experience, including 2+ years building and shipping production LLM/ML systems

Proven experience designing and deploying agentic systems (tool use, orchestration, multi-step workflows)

Strong Python proficiency with production-grade coding, testing, and deployment practices

Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, AWS Bedrock), including prompting, structured outputs, and function calling

Deep experience with evals and observability for LLM systems (accuracy measurement, regression detection, drift monitoring)

Experience building retrieval systems (RAG), working with vector databases and embedding models

Solid cloud infrastructure experience (AWS preferred), including APIs, containers, and serverless architecture

Strong system design mindset across LLM architecture (retrieval, memory, orchestration, tool use) with pragmatic tool selection

Ability to manage cost and latency tradeoffs in production AI systems

Clear communicator who can write design docs, explain tradeoffs, and collaborate cross-functionally

Ownership mindset: ships end-to-end and operates effectively in production environments

Experience in fintech, mortgage, or other regulated environments

Background in document AI, OCR pipelines, or structured data extraction

Familiarity with AWS AI services (e.g., Bedrock, SageMaker)

Experience with modern agent frameworks (e.g., LangGraph, CrewAI, AutoGen) and when to use them

Experience with modern data stacks (e.g., Snowflake, BigQuery, dbt)

Contributions to open source AI/ML projects

Experience supporting production systems on-call

Дополнительно

You are an applied AI engineer who ships. You’ve taken LLM-based systems and agentic workflows from prototype to production and understand what it takes to make them work in the real world—evals, observability, cost control, latency tuning, and continuous iteration

You have strong opinions on architectures and frameworks, shaped by hands-on experience, but you stay pragmatic—choosing the right tool for the problem rather than forcing a preferred approach. You stay current with emerging research and quickly translate what’s promising into production-ready solutions

You operate across the stack. You can design retrieval systems, implement tool use and orchestration, build evaluation harnesses, debug live issues, and clearly explain tradeoffs to both technical and non-technical stakeholders. You take full ownership and are driven by delivering systems that are reliable, scalable, and impactful

We believe people do their best work when they’re trusted, supported, and surrounded by others who are equally driven. That’s why this role includes a “work from the PLACE you work best” approach—at home, in an office, or on the move

Our competitive benefits include PTO as needed, comprehensive insurance coverage, a 401(k) match, stock option grants, and a stock purchase plan. Every team member is an owner, building the “PLACE” they are proud to call “my company.”