Principal Architect

Role Description

• Experience building agentic harnesses from scratch, including capabilities such as:
  • Tool use
  • Multi-step chaining
  • Reasoning
  • Streaming
  • Skills
  • Multimodal integration
  • RAG
  • Sandboxing
  • State management
• Experience designing, building, and operating production APIs and services, including:
  • RESTful APIs
  • Streaming APIs
  • Asynchronous workflows
  • Service boundaries
  • Versioning
  • Authentication/authorization
  • Error handling
  • Backward compatibility
• Demonstrated ownership of production systems, including:
  • Process improvements
  • Roadmap contributions
  • Defect resolution
  • Uptime and availability monitoring
  • Operational reliability
• Strong backend engineering fundamentals, with comfort working across:
  • Service design
  • APIs
  • Batch workflows
  • Orchestration
  • Observability
  • Production support
• Familiarity with evaluation techniques such as:
  • Creating and maintaining evaluation datasets
  • Running offline regression evals
  • Monitoring online production performance
  • Rubric-based scoring
  • Self-verification
  • Human-in-the-loop review
  • AI-as-judge methods
  • Quality/reliability analysis at scale
• Clear understanding of foundational machine learning and statistical concepts, including:
  • Sampling
  • Statistical significance
  • Overfitting/underfitting
  • Precision and recall
  • Quality tradeoff analysis
• Experience building and orchestrating large-scale batch workflows that use foundation models, including:
  • LLMs
  • VLMs
  • Pretrained open-source models
  • Deep learning models
• Ability to design systems that safely and reliably automate meaningful enterprise workflows using non-deterministic AI components.
• Strong judgment around:
  • Reliability
  • Failure handling
  • Observability
  • Human review
  • Operational safety
• Deep understanding of how to make systematic tradeoffs between:
  • Quality
  • Reliability
  • Latency
  • Cost
  • Explainability
  • User experience
• Ability to design pragmatic architectures that balance innovation with production readiness.
• Comfort working in environments where model behavior is non-deterministic and system design must account for:
  • Uncertainty
  • Evaluation
  • Monitoring
  • Graceful failure
• Experience with both lexical and embedding-based search methods.
• Ability to reason about:
  • Relevance
  • Ranking
  • Latency
  • Recall
  • Precision
  • Indexing strategy
  • Retrieval performance
• Experience working with foundation models and open-source LLMs beyond simple API calls.
• Familiarity with lower-level model behaviors and controls, including:
  • Temperature
  • Top-p sampling
  • Logprobs
  • Confidence scoring
  • Prompting strategies
  • Model selection tradeoffs
• Comfort and willingness to build front-end experiences using JavaScript/TypeScript and frameworks such as React.
• While the role is primarily backend and AI systems focused, the ability to contribute to user-facing product experiences is important.
• Willingness to work across the stack and own the end-to-end product experience is essential.
• Familiarity with tools such as FFmpeg, OpenCV, or similar media-processing libraries is a plus.

Qualifications

• 7+ years of programming languages such as Java, Golang, Python, JavaScript
• 2+ years of experience architecting, designing, and optimizing search and information retrieval systems at scale.
• 6 months to 1 year of hands-on experience building agentic products or solutions, including:
  • Tool-using agents
  • Conversational agents
  • Long-running agents
  • Reasoning/planning agents
  • Similar systems
• Experience with multiple modern agent frameworks is preferred. Specific frameworks are less important than demonstrated fluency, but exposure to tools such as:
  • OpenAI Agents SDK
  • LangGraph
  • Google ADK
  • SmolAgents
  • Comparable frameworks
• 1+ year of experience evaluating AI systems for quality, reliability, and safety at scale.
• 5+ years of experience shipping production software in an enterprise or consumer environment, not just prototypes or proofs of concept.
• OpenSearch or Elasticsearch experience is preferred, but comparable experience with other search and retrieval systems is sufficient.
• Expert experience, understanding, and knowledge of digital and broadcast production operations and workflows.
• Experience working with video, rich visual media, or multimodal AI systems.
• Strong knowledge of industry trends and best practices.
• Strong experience with the C4 model and other traditional design artifacts.
• Experience working in an Agile environment.

Requirements

• Experience with training, fine-tuning, or adapting models for domain-specific use cases using techniques such as LoRA, PEFT, or related approaches.
• Exposure to stateful software design patterns and streaming protocols such as WebSockets.
• Familiarity with client-side web technologies (React, Angular, JavaScript, CSS, HTML).
• 5+ years working with the AWS cloud.
• 1+ years working with the Azure cloud.
• Familiarity with continuous integration/delivery practices.
• Docker, Kubernetes experience a plus.
• BS in CS, EE or equivalent experience required.

Additional Information

All your information will be kept confidential according to EEO guidelines.

EEOC and Veteran Documentation: During employment, employees are treated without regard to race, color, religion, sex, national origin, age, marital or veteran status, medical condition or handicap, or any other legally protected status.

Please note: YOUR COOPERATION IS VOLUNTARY. INCLUSION OR EXCLUSION OF ANY DATA WILL NOT AFFECT ANY EMPLOYMENT DECISION.