Braeburn

AI Architect

Braeburn

full-time

Posted on:

Location Type: Hybrid

Location: Plymouth Meeting • Pennsylvania • 🇺🇸 United States

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Job Level

SeniorLead

Tech Stack

AirflowAWSAzureCloudDockerGoogle Cloud PlatformKafkaKubernetesPythonRaySparkSQL

About the role

  • Own the reference architectures for machine learning and Generative AI; define build-versus-buy and publish a 12–18-month AI platform roadmap aligned to business priorities.
  • Establish core services—data pipelines, feature store/model registry, prompt/model CI/CD, evaluation harnesses, observability (quality, safety, latency, cost), and automated rollback.
  • Design end-to-end solutions combining predictive models, large language models, and integrations with enterprise applications and data sources; ensure patterns for grounding, retrieval, and guardrails.
  • Stand up model risk and ethics guardrails; define evaluation metrics (factuality, hallucination rate, toxicity, bias), documentation, approvals, and live monitoring for drift.
  • Architect for AWS, Azure, and/or GCP and/or on-premise with secure networking, secrets management, and cost controls.
  • Partner with enterprise/platform teams to integrate AI into workflows, APIs, and UIs; ensure identity, authorization, auditability, and reliability SLAs.
  • Provide architectural governance, conduct design reviews, train users, and lead vendor/tool evaluations.
  • Track and selectively adopt advances in LLMs, agents/orchestrations, vector databases, and evaluation methods; run lightweight proofs to de-risk delivery.

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related STEM field.
  • 8+ years in solution/data/software architecture with 3+ years leading ML/GenAI systems to production.
  • Strong Python and SQL; deep familiarity with at least one major cloud’s AI/ML stack (AWS, Azure, or GCP).
  • Hands-on experience designing production ML/GenAI systems (RAG, evaluation, monitoring, and incident/rollback).
  • Solid grasp of data architecture (batch/stream), CI/CD, containerization (Docker/Kubernetes), and IaC.
  • Proven track record implementing security, privacy, and compliance controls (HIPAA; validation/audit in regulated settings).
  • Proficiency in programming languages such as Python and SQL.
  • Excellent communication skills and ability to articulate complex technical concepts to diverse audiences.
  • Problem-solving skills including analyzing, identifying root causes, and devising creative, effective solutions.
  • Strong project management skills: able to complete projects in a timely manner, plan and prioritize tasks while keeping leadership and stakeholders updated regularly on status.
  • Desirable: Life-sciences experience (clinical, PV, commercial, or RWE/RWD), including validation and Part 11 controls.
  • Desirable: Experience with model/experiment tooling (MLflow, Kubeflow, Weights & Biases), vector stores (pgvector, Pinecone, Weaviate), and orchestration (LangChain, LlamaIndex, Airflow).
  • Desirable: Big data/streaming (Spark, Kafka, Databricks).
  • Desirable: GPU/accelerator awareness for training/inference (e.g. CUDA basics, scheduling), or distributed compute (Ray).
  • Desirable: Relevant cloud certifications (AWS Solutions Architect, Azure AI Engineer, GCP Professional ML Engineer).
Benefits
  • Hybrid or Remote work arrangement

Applicant Tracking System Keywords

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

Hard skills
PythonSQLmachine learningGenerative AIdata architectureCI/CDcontainerizationIaCmodel risk managementevaluation metrics
Soft skills
communication skillsproblem-solving skillsproject management skills
Certifications
AWS Solutions ArchitectAzure AI EngineerGCP Professional ML Engineer