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OnsiteSeniorgeneral software

Java Full Stack Developer

Gravity Engineering ServicesChennai, Tamil Nadu, IndiaPosted 16 May 2026

Gravity Engineering Services is seeking a Full Stack Java Developer to design, build, and maintain software applications in their Chennai office. The role involves managing the full software development lifecycle, from architectural design to deployment on GCP. Candidates must have at least 4 years of development experience and expertise in a broad set of technologies including Java, Python, Angular, and cloud-native tools. You will work within an Agile environment to build scalable interfaces and backend microservices.

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Experience

4+ years

Function

Engineering

Work mode

Onsite, India

Company

Tier 2

What you will work on

Gravity Engineering Services is seeking a Full Stack Java Developer to design, build, and maintain software applications in their Chennai office. The role involves managing the full software development lifecycle, from architectural design to deployment on GCP. Candidates must have at least 4 years of development experience and expertise in a broad set of technologies including Java, Python, Angular, and cloud-native tools. You will work within an Agile environment to build scalable interfaces and backend microservices.

TAL's take

Quality 45/1002/5 clarityTier 2 company

Mid-tier company with a clearly defined but very broad, kitchen-sink tech stack.

JD lists an excessive number of specific GPC and devops tools while remaining broad on the actual product purpose.

Must haves

  • 4+ years of development experience
  • Proficiency in at least two coding languages or advanced proficiency in one
  • Experience with Java full stack development
  • Hands-on experience with Google Cloud Platform
  • Experience with CI/CD tools and Terraform
  • Proficiency in API development and microservices
  • Experience with SQL and Python

Tools and skills

javajsonai/mlgoogle cloud platformbig querydata flowdataprocdata fusionterraformtektoncloud sqlairflowpostgresqlpysparkpythonapiangularrest apissonarqubejenkinsdockeragile software development

Nice to have: flask, django, fast api, github copilot, test driven development.

About the company

unfamiliar company, default mid-tier

Posts mentioning Gravity Engineering Services

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[Thread] What is your favourite math equation?

TLDR: I was reading up on the Navier Stokes equations today and it is so elegant that it might be my favourite math equation. Equation 1: ∇u = 0 (conservation of mass) states that the divergence of the velocity vector u is zero, meaning there is no net change in fluid mass. Equation 2: ρ Du/Dt = -∇p + μ∇^2 u + ρF (conservation of momentum) expresses Newton's second law for fluid flow. It balances the acceleration of fluid particles (LHS) with internal forces (pressure and viscosity) and external forces (gravity or other external influences) on the RHS. This equation is foundational for modelling various fluid dynamics scenarios, from celestial bodies like stars and galaxies to F1 cars. Long Version: Here's how it works: Equation 1: ∇u = 0 (conservation of mass) So, u is velocity that can be represented as (u,v,w) vector, where u,v,w are x,y,z components of the vector. ∇u tells us that we need to do a partial derivative on u. So, ∇u = ∂u/∂x + ∂v/∂y + ∂w/∂z = 0 or, the partial derivative of every component wrt corresponding direction is 0. Equation 2: ρ Du/Dt = -∇p + μ∇^2 u + ρ F (conservation of momentum) LHS: Since, u is velocity, then Du/Dt is acceleration and ρ is density. Newton's second law, F = m x a, applies here. Wherein, Du/Dt is acceleration of fluid particles and m is the density of the fluid. RHS: -∇p + μ∇^2 are the internal forces of particles hitting into each other while F represents the external force. F in most cases is gravity, so one can replace it with g. However, if you put in electromagnetism then, you can combine Navier-Stokes with Maxwell's equations. This has over time led to the development of magnetohydrodynamics, ie how stars and galaxies form. You can model the growth of our sun with this. ∇p is our pressure gradient and represents the change in pressure. Essentially, fluids move from high pressure to low pressure. μ∇^2 represents viscous forces yielding from viscosity. Imagine this can model aerodynamics of F1 cars.

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