1. What is a Solutions Architect at Cohere?

At Cohere, the Solutions Architect (often aligned with Data Architecture leadership) is a pivotal role that bridges the gap between complex healthcare requirements and cutting-edge technology. You are not just building systems; you are defining the blueprint for how patient data is ingested, transformed, and utilized to improve clinical outcomes. This role sits at the intersection of technical strategy, regulatory compliance, and product innovation.

You will be responsible for designing enterprise-grade data platforms that are cloud-native and AI-enabled. Because Cohere operates in the highly regulated healthcare space, your work directly impacts our ability to maintain interoperability and security standards while scaling rapidly. You will guide product teams, mentor engineers, and ensure our architecture is robust enough to handle high-volume data systems without compromising on reliability.

This position offers a unique opportunity to shape the technical vision of a company transforming the prior authorization and patient journey landscape. You will work with a modern data stack—spanning AWS, Airflow, and dbt—and tackle challenges related to interoperability frameworks like FHIR and HL7. If you are a visionary architect who thrives on solving "impossible" data problems in a regulated environment, this role is designed for you.

2. Common Interview Questions

3. Getting Ready for Your Interviews

Preparing for an interview at Cohere requires a shift in mindset. You need to demonstrate not only technical depth but also the ability to lead conversations and structure ambiguity. The team looks for candidates who can take ownership of the interview process, acting as consultants rather than just test-takers.

Key Evaluation Criteria:

• Architectural Vision – You must demonstrate the ability to design scalable, long-term solutions. Interviewers assess whether you can look beyond immediate ticket requests to build compliance-first roadmaps that serve the business for years to come.
• Healthcare Domain Expertise – In this specific architecture role, knowledge of HIPAA, FHIR, and HL7 is critical. You will be evaluated on your ability to embed these regulatory standards into the very foundation of your platform designs.
• Technical Proficiency – Expect deep dives into the modern data stack. You need to show mastery over AWS data services (S3, Glue, Redshift), workflow orchestration, and data modeling (SQL/NoSQL) to prove you can execute on your high-level designs.
• Communication & Leadership – As a senior member of the architecture organization, you are expected to mentor engineers and communicate complex data strategies to cross-functional stakeholders. Interviewers look for clarity, influence, and the ability to work across time zones.

4. Interview Process Overview

The interview process for the Solutions Architect role at Cohere can be fluid. Based on candidate feedback, the process may sometimes feel less structured than at large legacy corporations. This is a feature of a fast-moving growth environment. You should expect a process that prioritizes conversation and problem-solving over rigid, scripted testing. You may encounter interviewers who are deeply technical but perhaps newer to interviewing; use this as an opportunity to drive the discussion and highlight your expertise proactively.

Typically, the process begins with a recruiter screen to align on pay bands and background. This is followed by a series of technical deep dives and behavioral rounds. You will likely meet with engineering leads, product managers, and potentially other architects. The discussions will oscillate between high-level system design and specific data engineering challenges. Because the team is growing, you might face scenarios where you need to explain "why" a certain architecture is necessary to someone who might be overwhelmed with current operational tasks.

The timeline above represents the typical flow, but be prepared for variations. The "Technical Deep Dive" and "System Design" stages often blend together, requiring you to sketch out architectures while simultaneously defending your technology choices. Use the visual to plan your energy; the middle stages are the most cognitively demanding.

5. Deep Dive into Evaluation Areas

To succeed, you must focus your preparation on the specific intersections of data engineering, architecture, and healthcare compliance. The following areas are heavily weighted in Cohere’s evaluation process.

Healthcare Data Ecosystems & Compliance

This is the differentiator for this role. You must prove you understand the constraints of the healthcare industry. It is not enough to design a fast database; you must design a compliant one.

Be ready to go over:

• Interoperability Standards – Deep knowledge of FHIR (Fast Healthcare Interoperability Resources) and HL7.
• Regulatory Security – Designing architectures that are HIPAA compliant by default.
• Data Governance – Strategies for managing patient consent, data lineage, and audit trails.

Example questions or scenarios:

• "How would you architect a data lake that ingests HL7 messages and converts them to FHIR resources in real-time?"
• "Describe your approach to handling PII/PHI in a cloud-native environment. How do you ensure encryption at rest and in transit?"

Modern Data Stack Architecture

Cohere relies on a specific set of tools. You need to demonstrate "broad command" of these technologies, moving beyond theory into practical implementation details.

Be ready to go over:

• AWS Data Services – Specifics on S3, Glue, Athena, and Redshift. Know when to use which service.
• Orchestration & Transformation – Experience with Airflow for workflow management and dbt for transformations.
• Performance Optimization – Tuning Redshift clusters, optimizing Glue jobs, and managing cost at scale.

Example questions or scenarios:

• "We have a bottleneck in our nightly ETL pipeline using Airflow and dbt. How would you debug and optimize this?"
• "Compare Redshift vs. Snowflake for our specific healthcare use case. Why would you choose one over the other given our AWS ecosystem?"

Data Modeling & Database Design

You will be expected to drive data modeling standards. This involves reviewing designs from other teams and ensuring they are robust.

Be ready to go over:

• Schema Design – Star schema vs. Snowflake schema, and data vault modeling.
• SQL vs. NoSQL – Choosing the right database engine for high-volume transactional systems versus analytical workloads.
• Indexing & Partitioning – Technical techniques for ensuring query performance on large datasets.

Example questions or scenarios:

• "Design a schema for a patient longitudinal record that needs to be accessed by both an AI model and a clinical dashboard."
• "How do you handle schema evolution in a production environment without downtime?"