Note: The job is a remote job and is open to candidates in USA. PLACE is a company operating at the intersection of real estate, technology, business services, and consumer markets. The Senior AI Engineer will design, ship, and operate production AI and agentic systems for document intelligence, workflow automation, and copilots, while owning LLM architecture, evaluation, observability, and optimization. The role also partners cross-functionally, mentors engineers, and evaluates models, vendors, and tools.
Responsibilities
- 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
Skills
- 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
Benefits
- “work from the PLACE you work best” approach—at home, in an office, or on the move
- PTO as needed
- Comprehensive insurance coverage
- A 401(k) match
- Stock option grants
- A stock purchase plan
Company Overview
Company H1B Sponsorship