Technical Manager — Java & Algorithms

We are looking for a hands-on Technical Manager who bridges deep engineering expertise with strong people leadership. You will drive high-impact product development, architect scalable systems, and mentor a team of engineers — all while staying close to the code. This role demands real proficiency in Java, algorithms, and mathematical problem-solving, not just project management.

Java Engineering

Deep expertise in Core Java, JVM internals, multithreading, concurrency, and modern Java (11+). Hands-on with Spring Boot, microservices, and distributed system design.

Algorithms & Data Structures

Strong command of DSA — graphs, trees, dynamic programming, sorting, search. Able to design and review algorithmic solutions for performance-critical systems.

Mathematical Problem Solving

Applies mathematical reasoning — probability, linear algebra, optimization, complexity theory — to engineer robust and efficient solutions in production environments.

Responsibilities

• Lead a team of 6–12 engineers, conducting code reviews, design discussions, and 1:1 coaching
• Architect and ship scalable backend services in Java with high performance and reliability
• Own technical roadmap, sprint planning, and delivery commitments for your team
• Evaluate and optimise algorithms for latency, throughput, and resource efficiency
• Collaborate cross-functionally with product, data, and infra teams on complex initiatives
• Identify and resolve technical debt while maintaining development velocity
• Interview, hire, and onboard strong engineering talent

Requirements

• 8+ years of software engineering experience, with 2+ years in a tech lead or management role
• Exceptional Java skills — able to write, review, and debug production-grade code confidently
• Strong algorithmic thinking; comfortable with whiteboard-level DSA problems
• Solid mathematical foundations: probability, statistics, complexity analysis, optimisation
• Experience with distributed systems, REST/gRPC APIs, messaging queues (Kafka/RabbitMQ)
• Proficiency with cloud platforms (AWS/GCP/Azure) and containerisation (Docker/Kubernetes)
• Excellent communication — fluent in both engineering depth and stakeholder conversations