# Initial Screening Interview with Shivani

## About Interview
:::danger
We are currently seeking **fully remote positions** only. If a recruiter inquires about a hybrid or on-site role, we kindly ask that it be declined.

Our minimum compensation requirement is **$65/hour** or **$120,000 per year**.
:::

:::info
**Meeting Date:** January 16 2026, 2:30 PM - 3:15 PM ET
**Meeting Url:** https://meet.google.com/nsa-gjsd-wig?hs=224
**Company:** MedBridge Inc.
**Recruiter:** Shivani Ahluwalia
**Phone Number:** 206.785.6901
:::

:::info
**My Name:** Vadim Shakhov
**Birthday:** 11/07/1996
**Address:** 347 Marion St, Brooklyn, NY 11233
**Email:** [e-mail]
**Phone Number:** [phone]
:::

## Job Description
:::info
Job Title: **Software Engineer III**

Job Type
Full-time

Description
Join the team shaping the future of healthcare! Medbridge is a dynamic software company working with the country’s largest healthcare providers to build technology solutions helping patients get better faster, while decreasing the overall cost of care. Our Development team is growing and looking for an enthusiastic Software Engineer III to join us!

We hire in the following states: AZ, CO, CA, FL, ID, GA, IL, NH, KS, MA, MI, MN, NC, NY, OH, OR, PA, SC, TN, TX, UT, VA, WA, WI.

We’re looking for a **Software Engineer III** to join our growing Patient Reported Outcomes team. This role is ideal for someone who thrives in a collaborative environment. In this role you will push Medbridge forward into our future as an insights company, driving outcomes for patients, clinicians and organizations alike. You will champion a strong engineering culture and advocate for best practices, making an impact across the entire organization.
**Why work at Medbridge?**
- We are mission driven. At Medbridge, our mission is clear - we want to help everyone move well, feel well, and live well.
- You’ll make an impact here. 300,000+ clinicians use our products daily, impacting millions of patients. In this role, you help create experiences that impact these important leaders.
- Our customers love Medbridge! We work with 9 of the top 10 Private Practice and hospital systems nationwide, and 6 of the top 10 home health organizations. have a nearly 100% client retention rate and are continuing that work in 2024 and beyond.

**Responsibilities:**
- Design, develop, and maintain scalable, reliable, and secure software solutions within the Medbridge platform, leveraging AI capabilities to enhance user experience and product functionality.
- Integrate AI-powered features and services into existing products, including natural language processing, predictive analytics, and intelligent automation solutions.
- Collaborate with cross-functional teams, including product managers, designers, data scientists, and other engineers, to define and implement new features with AI-driven insights.
- Architect and implement AI model deployment pipelines, ensuring seamless integration between machine learning models and production systems.
- Ensure code quality through rigorous testing, code reviews, and adherence to best practices, including AI model validation and performance monitoring.
- Continuously improve software engineering practices, processes, and tools to enhance team productivity and product quality, with focus on MLOps and AI development workflows.
- Mentor and provide guidance to junior engineers, fostering a culture of continuous learning and improvement in both traditional software development and AI technologies.

**Requirements:**
- 5+ years of professional software engineering experience, with a strong focus on SaaS applications and web services.
- 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and existing web applications.
- Hands-on experience integrating AI/ML services (e.g., OpenAI, Claude API, AWS Bedrock, Azure AI) into production applications.
- Experience with front-end and back-end technologies, including languages like Go, PHP, JavaScript and frameworks like Angular, with ability to build AI-enhanced user interfaces.
- Proficiency in working with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, LangChain, or similar) and implementing RAG systems.
- Experience and strong proficiency with MySQL or other relational databases, including vector databases for AI applications
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes)
- Demonstrated experience in prompt engineering, fine-tuning, and optimizing AI model performance in production environments.
- Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment and translate AI capabilities into business value.
- Experience in writing and maintaining unit, integration, and end-to-end tests to ensure software quality and reliability, including AI model testing and validation.
- A Bachelor's Degree in Computer Science, related field, or equivalent industry experience.

**Our Values:**
***Excellence:*** A job worth doing is a job worth doing RIGHT.
- We believe that excellence is never an accident. It’s the result of high intention, sincere effort, and intelligent execution.
- We are change-makers who push the boundaries of what is possible, continually reimagining patient care.
- We realize that our work impacts people’s health and demands that we hold ourselves to the highest possible standards.
- We know a good thing when we see it; when exceptional talent comes our way, we hire them and help them grow.
- We understand the value of time, and we give our best effort everyday because we have a day in which to give it.

***Fortitude:*** Our goals are big. Our dedication is bigger.
- We embrace ambitious and challenging projects with confidence in our ability to achieve them together.
- We are courageous as we venture into the unknown.
- We persevere in the face of difficulties.
- We do not let perfection be the enemy of progress; we focus on taking the next best step forward.
- We take ownership of our mistakes and of our successes, and we learn from both.

***Service:*** We work for something more important than ourselves.
- We care deeply about our colleagues, customers, and patients, ensuring our work at Medbridge has a lasting impact.
- We take a multi-disciplinary, data-oriented approach to solving problems.
- We lead with confidence and humility, embracing a servant-leadership mindset as we support and challenge one another to reach our shared goals.
- We know that if we do great work, we help people live healthier lives.

**Salary Range: $140,000 - $175,000**
At Medbridge, salary ranges are assigned to a job based on 3rd party salary benchmark surveys. Individual pay within this range is informed by the candidate's skills, capabilities and experience.

We embrace diversity and are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. No matter your background, your orientation, your identity expression, or whatever else makes you unique, if you want to raise the bar and join an amazing team of passionate people, then we'd love to work alongside you at Medbridge.
Now it’s your turn. If you liked what you’ve read and think Medbridge would be a great career choice for you, apply now and our Talent Acquisition team will follow up with you shortly after.
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## Intro Interview Guide

### ⚠️ Non-Negotiables (Set the Frame Early)
- **Work type:** Fully remote only
- **Compensation minimum:** $65/hour **or** $120,000/year
- If the role is **hybrid or on-site**, politely decline and exit early.

---

### 🧭 Objective of This Call
This is a **screening and alignment call**, not a technical deep dive.

Your goals:
1. Confirm whether **fully remote** is possible
2. Confirm **comp range alignment**
3. Decide quickly whether to proceed or exit

---

### “Tell me about yourself” (Requirements-Aligned)
> I’m a senior software engineer with over 9 years of experience building and operating SaaS platforms and API-driven web services. Most of my work has been in multi-tenant, production systems where reliability, scalability, and long-term maintainability are critical. I’ve spent several years contributing not just features, but also architectural decisions around service boundaries, data models, and scaling patterns.
>
> I work comfortably across the stack, building backend services in JavaScript and Python, and frontend applications using React and Angular-style frameworks, with earlier experience supporting PHP-based systems. I focus on building interfaces that surface complex data clearly and perform reliably under real-world constraints.
>
> Over the past few years, I’ve integrated AI and ML capabilities directly into production applications, including NLP-based classification, summarization, and AI-assisted workflows. I’ve worked with tools like OpenAI APIs and LangChain, implemented RAG-style systems that combine relational and vector-based data, and treated prompt design and model behavior as part of application logic rather than experimentation.
>
> I’m very deliberate about production readiness—using async processing, validation, monitoring, and testing to ensure AI features improve outcomes without compromising system stability. I tend to operate at the platform level, collaborating closely with product, design, and data teams to translate AI capabilities into concrete business value, rather than just shipping isolated features.

---

### What Enerflo is building (platform / architecture view)

> Enerflo is building the operating system for residential solar companies by acting as the central system of record across sales, financing, installation, and homeowner engagement. Architecturally, the platform sits at the center of a highly fragmented ecosystem, integrating with CRMs, solar design tools, lenders, installers, and internal operational services through APIs, webhooks, and event-driven workflows.
>
> The core challenge Enerflo solves is orchestration at scale: coordinating multiple organizations, tools, and lifecycle stages while enforcing data integrity and preventing downstream failures. The platform is designed to surface errors early, standardize workflows across diverse business models, and provide real-time visibility into project state from lead intake through PTO. This requires strong service boundaries, reliable integrations, and a data model that supports multi-tenant, multi-organization use cases without sacrificing performance or flexibility.

---

### “Explain about last project on Enerflo”
My role and impact at Enerflo (technical, performance-focused)

> At Enerflo, my primary responsibility was strengthening the core platform services that power search, pricing, financing, and project orchestration, with a strong focus on performance, scalability, and operational reliability. Rather than delivering isolated features, most of my work targeted systemic bottlenecks that affected multiple teams and workflows.
>
> On the backend, I worked extensively with NestJS and Node.js services running in a multi-tenant environment backed by PostgreSQL. I profiled slow endpoints and high-cardinality queries, identified inefficient joins and missing indexes, and reworked query patterns and schemas for read-heavy and mixed workloads. These changes reduced average query execution time by 30–50% on critical paths and improved overall API response times by ~20% under production load.

> I also reduced contention in synchronous request paths by introducing asynchronous processing where appropriate. For workflows involving AI inference and external integrations, I designed background job pipelines for prompt orchestration, batch inference, and result post-processing. By decoupling these workloads from request/response flows, we reduced request blocking by ~25% during peak traffic while keeping P95 latency stable.
>
> To ensure production safety, I implemented caching layers, strict input validation, and fallback strategies around third-party APIs, including ML/LLM services and external integrations. These changes reduced AI-related errors and degraded user experiences by ~30% and significantly lowered the blast radius of upstream latency spikes or partial outages.
>
> I placed a strong emphasis on observability and diagnosability. I introduced structured logging, metrics, and targeted alerts around inference pipelines, async jobs, and integration boundaries. This improved detection of failures and performance regressions and reduced incident investigation and resolution time by ~20%, while also lowering day-to-day operational noise.
>
> On the frontend, I worked on React-based applications with a focus on aligning UI behavior with backend constraints. I integrated AI-assisted features such as smart suggestions and assisted inputs in a way that respected latency budgets and failure modes. These changes reduced user task completion time by 12–15% and improved adoption of new features without introducing UI instability.
>
> Beyond direct implementation, I acted as a force multiplier across the engineering team. I standardized service patterns, reviewed architectural changes, and mentored engineers on performance tuning, async design, and integration boundaries. This reduced rework during code reviews by ~25% and helped teams ship changes faster with fewer regressions, while maintaining the stability expected of a platform that serves as the system of record for customer operations.

---

### “Do you have experience with Go?”

> Yes — I’ve used Go primarily for internal services and operational tooling where performance, concurrency, and reliability mattered more than rapid iteration.
>
> In one internal system management project, we used Go to build lightweight services responsible for background processing, health checks, and data synchronization between core SaaS services and external systems. These services handled high-throughput workloads using goroutines and channels, and were designed to be simple, predictable, and easy to operate.
>
> While Go wasn’t the primary application language across the entire platform, I’m comfortable working in it, reviewing Go code, and designing services that take advantage of its strengths—especially for infrastructure-adjacent or data-processing workloads.

---

### “What about PHP experience?”

> Earlier in my career, I worked extensively with PHP on internal management systems and customer-facing platforms. This included maintaining and extending PHP-based services that handled business logic, admin workflows, and third-party integrations.
>
> In several cases, these PHP systems were part of a larger ecosystem alongside newer services. I focused on stabilizing and improving them—adding validation, improving performance, reducing production issues—while enabling incremental modernization rather than risky rewrites.
>
> That experience gave me a strong appreciation for working in mixed-language environments and maintaining business-critical systems responsibly, which is something I still apply today when working with legacy or transitional systems.

---

### “What kind of frontend work have you owned?”

> I’ve owned major UI (User Interface) surfaces end-to-end, including dashboards, operational tools, and customer-facing workflows. That includes defining component architecture, building reusable systems in React and TypeScript, integrating complex APIs (Application Programming Interfaces), and optimizing performance under real production constraints. At Enerflo and iFit, I was directly responsible for shipping features that handled large datasets and near real-time updates without sacrificing UX (User Experience).

---

### “What’s your experience with AI / ML frameworks and RAG?”

> I’ve worked with AI frameworks and tooling such as LangChain, Hugging Face, TensorFlow, and PyTorch, primarily in applied settings rather than research.
>
> I’ve implemented RAG-style systems where application data is retrieved, validated, and injected into inference pipelines, with attention to relevance, freshness, and consistency of results.

---

### “How do you ensure quality and reliability, especially with AI?”

> I rely on strong testing, validation, and observability. That includes unit and integration tests for services, API contract testing, and monitoring production behavior.
>
> For AI features, I treat model outputs as probabilistic inputs—validating responses, testing edge cases, and monitoring performance drift so issues are detected early rather than silently impacting users.

---

### “How do you collaborate with backend teams?”

> Very closely. I regularly work with backend engineers building services in Node.js and Python, helping define and refine API (Application Programming Interface) contracts, handling asynchronous data flows and edge cases, and providing early feedback when data models or endpoints could impact frontend performance or usability. I focus on reducing tight coupling between layers and building predictable data flows so the UI (User Interface) remains stable as systems scale.

---

### ✅ Strong Match Areas (Direct JD Alignment)

#### SaaS & Platform Engineering
- 9+ years building scalable web services
- Multi-tenant SaaS systems with long lifecycles
- Strong focus on reliability and performance

#### AI-Enhanced Applications
- Production integration of LLM and ML services
- Prompt engineering, orchestration, and optimization
- RAG pipelines with validation and monitoring

#### Databases & Data
- Strong experience with relational databases (PostgreSQL, MySQL)
- Query optimization and schema design
- Vector-based retrieval alongside relational data

#### Cloud & Containers
- AWS-based deployments
- Dockerized services and Kubernetes
- Observability and safe deployment practices

#### Collaboration & Mentorship
- Cross-functional work with product and design
- Mentoring engineers on system design and AI patterns
- Translating AI capabilities into real business value

---

### 🚨 Remote-Only Clarification (Say Early)

**Exact wording:**
> Before we go too far, I want to be transparent about one thing. I’m currently only considering fully remote roles. I saw that Worth AI is remote-first with occasional travel — can you confirm that day-to-day work is fully remote?

If travel is mentioned:
> Occasional travel a few times per year is totally fine — I just want to confirm the role itself is remote-first.

---

### 🔄 If They Say It’s Not Fully Remote

> Thanks for clarifying. In that case, I don’t want to take up more of your time, since I’m focused exclusively on fully remote roles right now. I really appreciate the conversation and would be happy to reconnect if that changes in the future.

➡️ Exit politely. Do not negotiate further.

---

### 💰 Compensation Alignment (If Remote Is Confirmed)

> Just to align expectations early, for fully remote roles I’m targeting a minimum of $65 per hour or $120,000 annually. Does that fit within the range planned for this role?

If asked directly:

> That reflects my experience owning platform-level systems, improving performance and reliability, and acting as a force multiplier across teams.

---

### ❓ Smart Questions to Ask (Pick 2)

1. How does the Patient Reported Outcomes team validate and monitor AI-driven insights?
2. What would success look like for this role in the first six months?
3. How does Medbridge balance rapid iteration with the reliability required in healthcare?

---

### ✅ Strong Closing (If Aligned)

> This role sounds like a strong match for how I like to work—hands-on, platform-focused, and centered on building reliable, AI-enhanced systems in healthcare. If we’re aligned on remote work and compensation, I’d be very interested in continuing the process.

---

### 🧠 Personal Reminders

- This is a filtering call, not a sales pitch
- Speak calmly and concretely
- Emphasize system-level impact, not feature delivery
- Use numbers whenever possible
- Do not compromise on remote
- Align on compensation before next steps