Handshake

Forward Deployed Engineer I

Handshake
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4 months ago
Bengaluru, IndiaEntry Level

Responsibilities

  • Build and maintain production software supporting customer deployments.
  • Partner with senior engineers to design and deliver customer-facing solutions.
  • Collaborate with Engineering, Research, Product, and Operations teams on scalable production systems.
  • Develop full-stack applications using React, TypeScript, and modern backend technologies.
  • Translate customer requirements into reliable and scalable software solutions.
  • Improve system reliability, performance, and maintainability.

Requirements

  • At least two years of professional software engineering experience.
  • Strong programming skills with TypeScript, React, and modern backend development.
  • Understanding of relational databases such as PostgreSQL, APIs, and software engineering fundamentals.
  • Experience building and maintaining production software.
  • Familiarity with cloud platforms such as AWS or GCP.
  • Strong problem-solving, collaboration, and communication skills.
  • Preferred: experience with globally distributed engineering teams, customer-facing products or implementation projects, AI-powered applications or machine learning infrastructure, Docker, Kubernetes, CI/CD pipelines, or fast-growing startups.

Benefits

  • In-office role in Bengaluru, India.
  • Generous equity grant vesting over four years.
  • Housing bonus during the first year.
  • Performance bonus.
  • Medical insurance coverage.
  • Food credit for each in-person workday.
Handshake

About Handshake

10,000+ employees

Handshake builds a career network and recruiting platform that connects college students and recent grads with employers, sold as SaaS to universities and subscriptions/solutions to employers. Founded in 2014 and headquartered in San Francisco, it serves 1,600+ educational institutions and over 1 million employers. The company also operates Handshake AI, which partners with frontier AI labs on human data collection and evaluations for model training and post-training workflows.

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