Senior AI Engineer

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.

Must-Have:

• 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

Bonus if you have:

• 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

• →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

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.”