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Innovaccer Analytics

Healthcare data platform for outcomes optimization

Staff Engineer Full Stack - Model-View-Controller

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeNoida, Uttar Pradesh, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 8 years of software engineering experience, with a demonstrated track record of building and operating complex production systems.
  • Deep hands-on expertise in software engineering, system design, distributed systems, and cloud-native architectures.
  • Strong coding skills with depth in one or more areas and the ability to work effectively across the full stack.
  • Strong experience with Java, Python, Node.js, TypeScript, React, or equivalent modern technologies.
  • Strong understanding of databases, APIs, messaging, caching, observability, security, reliability, scalability, and cloud infrastructure.
  • Demonstrated experience driving architecture and technical initiatives across multiple teams.
  • Proven ability to take ambiguous, high-impact problems from problem definition through production.
  • Strong engineering judgment and ability to balance velocity, scalability, reliability, security, cost, and long-term maintainability.
  • Strong hands-on proficiency with AI coding tools, such as Cursor, Claude Code, GitHub Copilot, or equivalent AI coding agents.
  • Practical experience with the AI Development Life Cycle and AI-native development, including AI-assisted design, coding, testing, debugging, code review, evaluation, and iterative development.
  • Strong systems thinking and problem-solving skills, with the ability to reason across multiple layers of a technology stack.
  • Ability to influence technical decisions without relying on organizational authority.
  • Ability to work effectively across engineering, product, AI, and business stakeholders.
  • Demonstrated ownership, curiosity, bias for action, and continuous learning.

Responsibilities

  • Own and drive large, cross-team technical initiatives from problem definition and architecture through implementation, deployment, and production.
  • Design and build highly scalable, resilient, secure, and maintainable full-stack and distributed systems.
  • Solve complex technical problems that cross service, product, platform, and organizational boundaries.
  • Remain deeply hands-on by designing, coding, debugging, reviewing, and improving production systems.
  • Use AI coding agents and AI-assisted development across design, implementation, testing, debugging, refactoring, code review, and documentation.
  • Champion AI Development Life Cycle and AI-native engineering practices and help teams evolve development workflows to take advantage of AI.
  • Understand system-wide dependencies, trade-offs, failure modes, and customer impact beyond individual services and features.
  • Identify opportunities to simplify architecture, eliminate systemic technical debt, and improve engineering velocity, reliability, and developer experience.
  • Lead architecture and design discussions across teams and influence technical direction through engineering judgment and technical credibility.
  • Partner with Product, AI, Design, and Engineering leaders to translate ambiguous business and customer problems into technical strategies and executable solutions.
  • Establish reusable architectural patterns, engineering practices, and technical standards across teams.
  • Mentor Senior Engineers and SDE3s and help develop the next generation of technical leaders.
  • Proactively identify important problems before they become incidents, customer issues, or organizational bottlenecks.

Desired Qualifications

  • Hands-on experience building agentic AI applications or production AI workflows.
  • Experience with large language models, retrieval-augmented generation, tool calling, Model Context Protocol, AI agents, agent orchestration, or multi-agent systems.
  • Experience designing AI-native or agentic architectures.
  • Experience with AI evaluation, guardrails, observability, and runtime monitoring.
  • Experience helping organizations adopt the AI Development Life Cycle and AI-augmented engineering practices.
  • Experience with AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Temporal, or similar cloud-native technologies.
  • Experience defining engineering standards, architectural patterns, or platform-wide technical strategies.

About the Company

Innovaccer Analytics

Healthcare data platform for outcomes optimization

Innovaccer Analytics provides a Health Cloud platform that integrates and analyzes healthcare data for providers and pharmaceutical partners. The platform aggregates diverse data, applies care-management workflows, and delivers actionable insights to improve transitional care, lower 30‑day readmissions, and support primary-care services. It differentiates itself with demonstrated outcomes and strong customer-experience ratings, including measurable value for clients. Its goal is to improve patient health outcomes and financial performance by delivering scalable data integration and analytics across the healthcare ecosystem.

Company size
1,001-5,000
Company stage
Private
Total funding
$653.1M
Headquarters
San Francisco, CA
Founded
2012

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