
AI Architect
Reports to: Chief Financial Officer
Location: Plymouth Meeting HQ (Hybrid) or Remote
Company Overview:
Braeburn is dedicated to delivering solutions for people living with the serious consequences of opioid use disorder. At Braeburn, we challenge the status quo and champion transformation of the management of opioid use disorder (OUD) by partnering with the community to create a world where every person with OUD gets the best possible care and opportunity to reach their full potential. Our shared commitment to innovation on behalf of patients enables us to help people with OUD begin and sustain recovery.
At Braeburn, there are opportunities to contribute to our purpose every day. We value authenticity and strive to amplify all voices. Our culture empowers everyone to be successful and unleashes our full potential.
Position Summary:
We are seeking a highly skilled AI Architect to lead the enterprise-wide design and implementation of cutting-edge AI and orchestrated multi-step workflows. This role is responsible for translating business challenges into robust, scalable, and secure AI architectures. This individual will need to collaborate with cross-functional teams, including functional stakeholders and Subject Matter Experts (SMEs), to deliver end-to-end AI systems from conception to deployment and lifecycle management.
This role is a blend of strategy and hands-on prototyping and architectural ownership (not day to day engineering), requiring expertise in machine learning (ML), data architecture, and cloud technologies. The AI Architect is responsible for developing compliant AI platforms that solve business problems and drive innovation.
Specific Duties:
- Architecture & Roadmap: 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.
- Platform & Machine Learning Operations/Large Language Model Operations: Establish core services—data pipelines, feature store/model registry, prompt/model Continuous Integration/Continuous Delivery, evaluation harnesses, observability (quality, safety, latency, cost), and automated rollback.
- Solution Design: Design end-to-end solutions that combine predictive models, large language models, and integrations with enterprise applications and data sources; ensure patterns for grounding, retrieval, and guardrails.
- Governance & Responsible AI: Stand up model risk and ethics guardrails; define evaluation metrics (factuality, hallucination rate, toxicity, bias), documentation, approvals, and live monitoring for drift.
- Cloud & Infrastructure: Architect for Amazon Web Services, Azure, and/or Google Cloud Platform and/or on-premise, with secure networking, secrets management, and cost controls (Financial Operations).
- Integration: Partner with enterprise/platform teams to integrate AI into workflows, Application Programming Interfaces, and User Interfaces; ensure identity, authorization, auditability, and reliability Service Level Agreements.
- Technical Leadership: Provide architectural governance, conduct design reviews, train users, and lead vendor/tool evaluations.
- Innovation & Research: Track and selectively adopt advances in large language models, agents/orchestrations, vector databases, and evaluation methods; run lightweight proofs that de-risk delivery.
Skills:
- Proficiency in programming languages such as Python and SQL.
- Excellent communication skills and the ability to articulate complex technical concepts to diverse audiences and align executives, SMEs, with clear trade-offs.
- Problem-Solving skills including analyzing, identifying root causes, and devising creative, effective solutions.
- Adaptability and learning agility.
- 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.
Education/Experience:
Required
- 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).
Desirable
- Life-sciences experience (clinical, PV, commercial, or RWE/RWD), including validation and Part 11 controls.
- Experience with model/experiment tooling (MLflow, Kubeflow, Weights & Biases), vector stores (pgvector, Pinecone, Weaviate), and orchestration (LangChain, LlamaIndex, Airflow).
- Big data/streaming (Spark, Kafka, Databricks).
- GPU/accelerator awareness for training/inference (e.g. CUDA basics, scheduling), or distributed compute (Ray).
- Relevant cloud certifications (AWS Solutions Architect, Azure AI Engineer, GCP Professional ML Engineer).
What success looks like (6–12 months)
- Published and adopted AI reference architecture and security/validation patterns.
- One or more high-impact GenAI/ML use cases live in production with measurable outcomes (e.g., cycle-time reduction, accuracy/factuality improvements, cost targets).
- Operational LLMOps/MLOps: model/prompt registry, automated evaluations, monitoring dashboards, and on-call processes.
- Documented governance aligned to HIPAA/GxP/Part 11, with audit-ready artifacts and change control.
Braeburn is committed to ensuring equal employment opportunity for all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, military/veteran status, age, disability, or any other category/characteristic protected by law (collectively, "Protected Categories"). In fact, we encourage all underrepresented backgrounds to apply for any open job positions with the company.
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