Engineering Manager

Company Description NikahForever is India’s most trusted Community Matrimony platform, focused on making marriages convenient and meaningful. The company is dedicated to building a stronger community by enabling genuine connections and long-term relationships. Since its founding, NikahForever has supported over 75,000 successful stories and attracted more than 4,000,000 members. The platform allows people to find a compatible partner in three simple steps: Register, Search, and Connect. Powered by AI-based algorithms, NikahForever is transforming how individuals approach and experience marriage.
Software Development Engineer I (SDE-1)
Location: [Mohan Estate, New Delhi] |
Experience: 2 years | Type: Full-time
The Role
We're looking for an engineer who can think independently, solve difficult problems, and turn ideas into reliable production software.
You won't always get a detailed specification or a step-by-step implementation plan. You'll get a problem, its context, and the freedom to figure out how to solve it. You'll learn unfamiliar systems, make practical engineering decisions, build and test solutions, and take ownership of your work from implementation through deployment.
We're AI-native. You'll use AI coding agents and modern engineering tools to accelerate development, explore unfamiliar codebases, debug issues, and automate repetitive work. You'll remain accountable for the correctness, security, and reliability of everything you ship.
We don't hire based on familiarity with a particular programming language, framework, or technology stack. We value strong fundamentals, problem-solving ability, learning speed, engineering judgment, and the ability to deliver working software.
What You'll Do
Build and ship software: Turn product requirements and business problems into working, reliable software that delivers measurable value.
Own features end to end: Understand requirements, explore possible solutions, implement features, write tests, deploy changes, and fix issues after release.
Solve engineering problems: Break down ambiguous problems, evaluate trade-offs, reason through edge cases, and develop practical solutions without relying on step-by-step instructions.
Work across domains: Contribute to backend systems, APIs, databases, infrastructure, integrations, data-intensive applications, and AI-powered workflows as the problem requires.
Navigate unfamiliar systems: Understand existing codebases, investigate how components interact, and adapt to new technologies without treating unfamiliarity as a blocker.
Debug and investigate: Reproduce failures, analyze logs and system behavior, identify root causes, and implement fixes that prevent recurring problems.
Make sound technical decisions: Consider correctness, performance, reliability, maintainability, security, cost, and implementation complexity when choosing a solution.
Use AI-native engineering workflows: Leverage AI coding agents for exploration, implementation, debugging, testing, and refactoring. Review their output critically and verify that solutions work as intended.
Automate repetitive work: Identify inefficient manual processes and build tools or automations that improve productivity and reduce operational effort.
Collaborate and take ownership: Participate in design discussions, code reviews, and technical problem-solving. Communicate blockers early and incorporate feedback constructively.
Continuously improve: Learn from production issues, measure the impact of your work, and improve the quality and reliability of the systems you build.
Examples of Problems You'll Tackle
Build a new product capability from an ambiguous requirement, making appropriate implementation and design decisions along the way.
Investigate a slow or unreliable service, identify its bottlenecks, and improve its performance and resilience.
Design a reliable workflow for processing tasks asynchronously, handling failures, and preventing data inconsistencies.
Build an AI-powered workflow that uses external tools and APIs to automate a multi-step business process.
Investigate a production failure in an unfamiliar codebase, identify the root cause, and ship a thoroughly tested fix.
Develop an internal tool that removes repetitive manual work and measure the resulting improvement in efficiency.
What We're Looking For
Must Have
Strong engineering fundamentals and the ability to reason systematically about unfamiliar problems.
A solid understanding of data structures, algorithms, computational complexity, and essential software design principles.
The ability to write clear, maintainable, and testable code, regardless of the programming language or technology used.
A practical understanding of how software components interact, including APIs, databases, networking, and operating systems.
The ability to break down complex tasks into smaller, verifiable steps and make progress without constant supervision.
Comfort navigating unfamiliar codebases, learning new technologies, and adapting to different technical environments.
A disciplined approach to debugging, testing, handling edge cases, and investigating the root causes of failures.
The judgment to make reasonable technical trade-offs and recognize when a solution is unnecessarily complex or unreliable.
Practical familiarity with AI coding tools or a demonstrated willingness to adopt them, along with the ability to validate generated code critically.
Strong ownership, curiosity, attention to detail, and a bias toward finishing and shipping work.
The ability to communicate technical decisions clearly, ask useful questions, and take feedback constructively.
Evidence of practical engineering ability through projects, internships, research, open-source contributions, or other work demonstrating problem-solving and implementation skills.
Strong Plus
B.Tech/B.E. in Computer Science (CS), Information Technology (IT), Electronics and Communication Engineering (ECE), Electrical Engineering (EE), or a related field, ideally from a strong engineering program.
Experience building and deploying software that solves a real problem for actual users.
Experience diagnosing performance issues, improving reliability, or resolving difficult technical bugs.
Exposure to production systems, cloud environments, automated testing, deployment, monitoring, or incident investigation.
Experience working across multiple technical domains or adapting to unfamiliar technology stacks.
Projects involving AI-powered applications, LLMs, autonomous agents, or workflow automation.
Practical experience using AI coding agents to accelerate development while maintaining strong quality standards.
Contributions to products, tools, research, or open-source projects that demonstrate initiative beyond completing tutorials.
Evidence of independently taking an idea from initial problem discovery to a working, tested solution.
How You'll Be Evaluated
Engineering and project review: Walk us through something you've built, the problem it solves, your personal contribution, and the decisions you made.
Practical problem-solving: Work through an engineering problem that assesses reasoning, implementation, edge cases, and correctness rather than familiarity with a particular technology.
Code implementation and debugging: Build or modify a solution in a practical environment, investigate failures, and demonstrate how you test your work.
System design and reasoning: Approach an open-ended problem, explain the major components, evaluate trade-offs, and reason about reliability and future growth.
AI-assisted engineering exercise: Use an AI agent to explore, build, or debug a solution while demonstrating how you guide, inspect, and verify its work.
Ownership and learning discussion: Discuss a difficult problem you've solved, a mistake you've made, how you handled feedback, and how you approach unfamiliar technology.
Why Join
Own meaningful engineering problems and contribute directly to product outcomes.
Work across different technical domains rather than being restricted to a single technology stack.
Learn how production systems are designed, built, deployed, monitored, and scaled.
Use AI coding agents and modern engineering workflows to solve real-world problems.
Develop strong engineering judgment through practical challenges, code reviews, and production ownership.
Work in an environment that values initiative, learning speed, technical depth, and measurable impact.
[Compensation range, equity, benefits, learning budget, and AI tooling budget.]
How to Apply
Send your resume, GitHub or equivalent technical portfolio, and 1–2 examples of systems or projects you've built, shipped, or improved.
Please briefly describe:
A difficult engineering problem you've solved and how you approached it.
Something you've built that demonstrates your ability to turn an idea into a working solution.
An example of how you've learned an unfamiliar technology or used AI tools to improve y

Work arrangement
No