PracticeSuite is a fast-growing healthcare technology company dedicated to simplifying healthcare operations through innovative software solutions. Founded in Silicon Valley and headquartered in Tampa Bay, Florida, the company serves more than 92,000 healthcare users across the United States. PracticeSuite provides an integrated platform spanning Practice Management, Electronic Health Records (EHR), Revenue Cycle Management (RCM), Patient Engagement, and AI-powered healthcare solutions.

With global teams across the US, India, and Costa Rica. Headquartered in Tampa Bay, Florida, with operations in India including Kochi, Mumbai.

Responsibilities

- Governed agentic lifecycle: Design and run the AI development lifecycle with clear inputs, outputs, and review gates at each stage (PRD, BRD, prototype, HLD, LLD, tests, code, security/compliance). Guardrails and artifacts are part of how the team works.
- Solution architecture: Architect solutions for production SaaS — primarily self-hosted, Java-based systems — including services, data, integration, and the infrastructure implications of running in production.
- Quality: Build quality into the path: component tests, test harnesses, and evals. Automated tests are created in parallel with implementation, not after the fact.
- Agentic platform: Select and implement agentic frameworks, skills, and tooling. Manage context and cost so agentic development can run at scale.
- Repeatable patterns: Turn the first live project into reusable skills, templates, and infrastructure the wider engineering organization can adopt.
- Hands-on delivery: Write and review design and code at a senior-developer standard. Until additional engineers join, you and the product partner are the delivery team.
- Collaboration:



Partner closely with the product/business hire (problem framing, artifacts, prompting, and human-in-the-loop). Work with security, compliance, and other engineering teams as solutions move toward production.
- Team build: Help hire and mentor two AI-ready engineers as the cell grows.

Required Qualifications

- Production SaaS: Sound grasp of production SaaS systems using self-hosted, non-cloud technologies. Java strongly preferred.
- System architecture: 3 or more years as Architect or technical lead role. System architecture including infrastructure literacy: how designs are hosted, integrated, observed, and failed over.
- Quality: Grounded foundation in component testing, test harnesses, and making quality executable.
- AI: At least 1 year of direct AI and Agentic development experience. Experience and strong knowledge of AI, including reinforcement learning and related methods — not only wrapping a chatbot API.
- Agentic development and AI development lifecycle: you can name the inputs, outputs, and review gates at each stage and have used them to ship.
- Context and cost: Experience managing context and cost for agentic development at scale (context engineering, routing, caching, evals).
- Engineering craft: Senior-developer command of SOLID, DRY, and production engineering practices. You write and review code.
- Frameworks: Hands-on with agentic frameworks such as LangChain,



LangGraph, or equivalent (including custom harnesses).
- Working style: Highly responsible, dynamic, and an excellent communicator. Comfortable working from Navi Mumbai with US-based leadership, taking limited direction, and still delivering.

Nice to Have

- Java and services: Spring Boot, Maven or Gradle, REST/JSON APIs, OpenAPI. Experience with multi-tenant or schema-per-customer SaaS.
- Data: Oracle and/or PostgreSQL in production. Redis or similar for caching. Familiarity with reporting/analytics stacks (e.g. Metabase) a plus.
- AWS: Working knowledge of core services we use and adjacent ones: EC2, VPC, IAM, S3, RDS, CloudWatch. Ability to reason about hybrid self-hosted plus cloud designs.
- Containers and delivery: Docker in production. ECS or Kubernetes a plus. CI/CD (Jenkins, GitHub Actions, GitLab CI, or similar).
- Testing and evals: JUnit, Testcontainers, API contract tests. UI or prototype automation (e.g. Playwright). LLM eval harnesses (LangSmith, Promptfoo, or custom evals).
- Agentic and AI platform: LangGraph, tool calling, MCP, RAG / vector stores, spec-driven development, structured outputs, model routing.
- Observability: Logs, metrics, and traces in production (Prometheus, Grafana, OpenTelemetry, Graylog, or equivalent).
- UI delivery: React, Next.js, and Flutter.
- Healthcare and security: Healthcare, HIPAA, HITRUST, SOC 2, or similar regulated environments. FHIR or HL7 familiarity a plus.

Location: Navi Mumbai | Reports to VP of Engineering | Full time Experience: 3+ years as Architect or Technical Lead role and at least 1 year of direct AI & Agentic development experience

Work Shift Timing: US Shift (11AM to 7 PM)

📌 Architect, Agentic Delivery (Mumbai)
🏢 Practicesuite
📍 Mumbai