Senior AI Engineer

PLACE

Senior AI Engineer shaping the future of AI-powered mortgage technology at PLACE. Collaborating with teams to deliver AI solutions for data-driven decisioning and workflow automation.

Posted 5/20/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $90,000 - $150,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

PTO as needed
Comprehensive insurance coverage
401(k) match
Stock option grants
Stock purchase plan

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonLLM systemsagentic systemsproduction-grade codingtestingdeployment practicesretrieval systemsvector databasesembedding modelscloud infrastructure

Soft Skills

clear communicatorownership mindsetmentoringcollaborationsystem design mindsetcost managementlatency management