7 days ago
Remote, United StatesSenior
Base Salary
$125k - $182k/yr
Responsibilities
- Lead discovery with business and technology stakeholders to understand objectives, constraints, systems, and integration points.
- Document current-state architectures and define target-state designs, system context diagrams, component designs, integration patterns, and data flows.
- Design cloud-compatible and cloud-native applications using microservices, serverless, and event-driven patterns where appropriate.
- Create cloud migration strategies, roadmaps, and designs for applications and data workloads.
- Design AI, ML, and Generative AI solutions, including model integration, model serving, RAG, tool and API integration, prompt and context management, and evaluation approaches.
- Define AI platform reference architectures covering data pipelines, feature and embedding generation, vector storage, model endpoints, and enterprise API integrations.
- Establish MLOps and AI operations practices for versioning, deployment, monitoring, drift detection, incident response, and cost management.
- Incorporate identity, access control, encryption, secrets management, secure networking, audit logging, privacy, explainability, safety, compliance, and model risk controls.
- Communicate tradeoffs, risks, and value to drive stakeholder alignment and governance approval.
- Support testing and validation teams and help resolve architecture-related issues during development, UAT, and production.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Business, or equivalent practical experience.
- At least 5 years of experience in agile software delivery environments with increasing architecture and design responsibility.
- Experience designing distributed systems using microservices and/or serverless patterns.
- Experience integrating AI and ML capabilities into applications, including model-serving considerations and data dependencies.
- Experience with one or more of Java, Python, Node.js, or Scala.
- Experience with SQL and NoSQL data persistence technologies.
- Experience with AWS, Azure, or Google Cloud and core cloud design patterns.
- Working knowledge of automated testing, deployment automation, and DevOps practices.
- Strong communication skills and the ability to translate business needs into technical direction.
- Preferred experience with GenAI and LLM solutions, RAG, embeddings, evaluation, and production monitoring.
- Preferred experience with AWS SageMaker, Amazon Bedrock, Azure AI, Azure OpenAI, or Google Vertex AI.
- Preferred infrastructure-as-code experience with Terraform or CloudFormation.
- Preferred experience with Docker, Kubernetes, ECS, or EKS.
- Preferred experience with vector databases, search technologies, indexing and retrieval patterns, observability, PL/SQL, data modeling, responsible AI, governance, and AI security.
Benefits
- Medical, dental, vision, and life insurance.
- 401(k) retirement plan with matching contributions of up to 6%, potential discretionary contributions, financial advisory services, and investment options.
- Tuition reimbursement of up to $5,250 per year.
- Generous paid time off upon hire, including ten paid company holidays and three floating holidays annually.
- 16 hours of paid volunteer time per calendar year.
- Paid parental leave, short- and long-term disability, and FMLA leave programs.
- Business Resource Groups open to all employees.
- Flexible work environment and fluid internal career paths.
- For remote or hybrid work, reliable high-speed wired internet and an appropriate home workspace are required; necessary computer equipment will be provided, and office work may be required if conditions are inadequate.
Categories
Solutions Engineering
