Software Engineer (LLM Platform Engineer) (0059-0015)

Designing and implementing robust abstractions and interfaces, including validating probabilistic and non-deterministic LLM outputs into deterministic reasoning systems that drive business actions, with AST parsing and Pydantic model validation.

Developing integration tests for backend in Python using PyTest.

Developing and maintaining the core cognitive architecture that enables Clara to navigate the complexities of real-world commercial use and meet reliability standards, including building frontend components using React with Redux (actions, reduces, selectors, middleware).

Building and optimizing prompts and production-grade systems for leveraging large language models (LLMs) to power autonomous agent interactions and developing RESTful API services using Flask.

Creating elegant, developer-friendly APIs and internal platforms that support Clara's scheduling workflows.

Implementing systems with strong focus on reliability, observability, and maintainability for mission-critical business applications.

Developing and applying testing methodologies specifically designed for systems with probabilistic outcomes to create deterministic and probabilistic test suites integrated into the CI/CD pipeline.

Collaborating closely with founders, ML engineers, and other stakeholders to architect solutions and iterate quickly, using Github Issues and Github Pull Request to manage collaboration and code reviews.

Making thoughtful technical trade-offs that balance experimentation with production-grade reliability by conducting systematic prompt evaluation and benchmarking using structured test sets and leveraging multiple LLM providers, including OpenAI and Google via REST API endpoints.

Designing state management systems to handle complex conversation flows and agent decision-making.

Testing and debugging browser developer tools to maintain reliability and consistency.

Implementing containerization, deployment automation, CI/CD practices to support the platform, container-based build environments using Docker, and orchestrating automated deployments through platforms including Kubernetes.

Document technical decisions and communicate architectural choices across the organization using Github Pull Request and develop custom metrics and record dashboards for stakeholders showing system usage trends, API performance, and pipeline reliability.

Staying current with advances in LLM orchestration tools and frameworks to continuously improve Clara's capabilities, including designing and implementing an internal-facing telemetry framework using OpenTelemetry and OpenSearch.

Education and Experience Requirements

Bachelor’s Degree (or foreign educ. equiv.) in Statistics, Computer Science, Data Science or a closely related field plus three (3) years’ experience in the job offered or a related occupation.

Special Skills Requirements

Experience must include: a) Developing integration tests for backend in Python using PyTest. b) Building frontend components using React with Redux (actions, reduces, selectors, middleware). c) Testing and debugging of browser developer tools to maintain reliability and consistency. d) Using Github Issues and Github Pull Request. e) Optimizing prompts for large language models (LLMs) and developing RESTful API services using Flask. f) Implementing container-based build environments using Docker and orchestrating automated deployments through platforms including Kubernetes. g) Validating probabilistic and non-deterministic LLM outputs with AST parsing and Pydantic model validation. h) Designing and implementing an internal facing telemetry framework using OpenTelemetry and OpenSearch.

May telecommute.

Please copy and paste your resume in the email body (do not send attachments, we cannot open them) and email it to candidates at placementservicesusa.com with reference #0059-0015 in the subject line.

Thank you.