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Senior Software Engineer II - (AI Core Platform)

United States · remote · Salary not listed

Role overview

As a Senior Software Engineer II at Aledade, we maintain, improve, and expand our web application and data pipelines. We're looking for engineers who know that writing new code is not always the solution to a problem, but when technological changes are needed they create secure, maintainable, performant, correct, scalable, and stable solutions to the complex and unique challenges in our corner of the healthcare industry.

They embrace strategies that minimize risk, leaning towards observability, alerting, metrics, high test coverage, and frequent releases that incrementally build value.

This role will focus on platform reliability, observability/OTEL, auth + networking integrations, runtime scalability, and future memory/governance platform work.

Primary Duties:

Develop and implement scalable and performant solutions.
Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes.
Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work.

Minimum Qualifications:

BS/BTech (or higher) in Computer Science, Engineering or a related field.
6+ years experience as an engineer building full-stack web applications as part of a cross-functional team.
3+ years of experience working with SQL or other database querying language on large multi-table data sets.
3+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.
3+ years of experience coaching other engineers.

Responsibilities:

Deep AWS + infrastructure experience.
Networking and distributed systems knowledge.
Auth/authz experience (IAM, OAuth, API gateways, service-to-service auth, etc.).
Experience working with enterprise security/compliance requirements.
Some familiarity with LLM/agent ecosystems (Bedrock, LangGraph, LiteLLM, MCP, OpenAI APIs, Claude Code, etc.).
Improve AI/ML infrastructure for model development, training, and deployment, with a focus on large language models and other generative AI architectures.
Design multi-year vision, shaping the direction of crucial generative AI areas - text generation, image synthesis, multimodal models, and personalized content creation.