Java Developer

Job Description below:

Software Engineer-Java

• Experience in Core Java 5.0 and above, Data Structures, OOPS, Multithreading, Algorithms, Collections, Unix/Linux
• Possess good architectural knowledge and be aware of enterprise application design patterns.
• Should have the ability to analyze, design, develop and test complex, low-latency client-facing applications.
• Good development experience with RDBMS
• Good knowledge of multi-threading and high-volume server-side development
• Basic working knowledge of Unix/Linux
• Excellent problem solving and coding skills in Java
• Strong interpersonal, communication and analytical skills.
• Should have the ability to express their design ideas and thoughts.

Job Brief-

·       Understand product requirements and come up with solution approaches

·       Build and enhance large scale domain centric applications

·       Deploy high quality deliverables into production adhering to the security, compliance and SDLC guidelines

AI Engineer — Vertexcover Labs

Who We Are

Vertexcover Labs is an employee-focused, engineer-run software studio. We partner with fast-growing, funded startups around the world—Rephrase.ai, Dhiwise, Dunzo, Dubdub, Xapo, Arintra etc.—to crack their toughest engineering problems. Everyone is an individual contributor; no management layers. Engineers choose the projects they work on, see each project's P&L, and share directly in the profits.

Whether it's building multi-agent systems for production, scaling ML pipelines across GPU clusters, or shipping RAG-powered products that end-users rely on—we solve hard AI problems for real companies.

A Few Problems We Are Currently Working On

• AI Agents Test-authoring agents that convert natural language into e2e tests.
• Ad-performance agents that learn what works for your brand and generate winning creatives automatically.
• Scale + MLOps Optimise ML pipelines and fix autoscaling by applying queuing theory while juggling CPU / GPU memory contention.
• RAG & Knowledge Systems Design and deploy retrieval-augmented generation pipelines—chunking strategies, embedding models, reranking, and evaluation loops.
• AI Video & Image Processing Build rendering pipelines, diffusion-model integrations, and real-time video processing at scale. You'll own at least one project like these—design, build, iterate.

Signals You're Probably the Right Fit

• Strong in at least one other language (Python, Go, Rust, TypeScript, Java …); happy to learn more.
• First principle understanding of how LLMs, embeddings, vector databases and AI Agents work
• Evidence of shipping real AI-powered software—OSS, side projects, or production features.
• Comfortable navigating the fast-moving AI landscape—papers, new model releases, evolving APIs.
• Clear written & spoken communication; async collaboration is our default.
• Self-directed—you ask for context, not permission.

How We Operate

• Project choice. Engineers vote on which engagements we take.
• Stack agnostic. We pick tools that fit the job, not the résumé.
• Pragmatic craftsmanship. Durable design, no gold-plating.
• Transparent economics. Know what your work is worth, share in the profits.
• Remote-native. Async by default; sync when it helps.

Hiring Process (Lean & Human)

1. 2–3 technical deep-dives with future teammates.
2. 30-minute culture chat.
3. Offer. No LeetCode marathons, no trick puzzles.

We read every application and reply to all candidates.

1. Need to have an understanding of Elastic Search, Kafka, mongo DB, etc.

2. Should have experience of Jupter noobooks, data bricks

3. Java, Pythons

4. Senior level, 5-10 years of experience

5. It is important they have those skills so that they can take over current work. There are codes written in both Java as well as Python. (Java is legacy but that is the main search engine code). So it will be counter-productive if engineers hired have experience in both.

6. Excellent communication, analytical, research, grasping skills

• 2+ years of experience in using Java/J2EE tech stacks
• Good understanding of data structures and algorithms.
• Excellent analytical and problem solving skills.
• Ability to work in a fast paced internet start-up environment.
• Experience in technical mentorship/coaching is highly desirable.
• Understanding of AI/ML algorithms is a plus.

• Preferred Education & Experience:

• Bachelor’s or master’s degree in Computer Engineering, Computer Science, Computer Applications, Mathematics, Statistics or related technical field or equivalent practical experience. Relevant experience of at least 3 years in lieu of above if from a different stream of education.

• Well-versed in and 5+ years of hands-on demonstrable experience with:
  ▪ Object Oriented Modeling, Design, & Programming
  ▪ Microservices Architecture, API Design, & Implementation
  ▪ Relational, Document, & Graph Data Modeling, Design, & Implementation

• Well-versed in and hands-on demonstrable experience with:
  ▪ Stream & Batch Big Data Pipeline Processing
  ▪ Distributed Cloud Native Computing
  ▪ Serverless Computing & Cloud Functions

• 5+ years of hands-on development experience in Java programming.

• 3+ years of hands-on development experience in one or more libraries & frameworks such as Spring Boot, Apache Camel, Akka, etc.;
  extra points if you can demonstrate your knowledge with working examples.
  2+ years of hands-on development experience in one or more Relational and NoSQL datastores such as Amazon S3, Amazon DocumentDB, Amazon Elasticsearch Service, Amazon Aurora, AWS DynamoDB, Amazon Athena, etc.

• 2+ years of hands-on development experience in one or more technologies such as Amazon Simple Queue Service, Amazon Kinesis, Apache Kafka, AWS Lambda, AWS Batch, AWS Glue, AWS Step Functions, Amazon API Gateway, etc.

• 2+ years of hands-on development experience in one or more technologies such as AWS Developer Tools, AWS Management & Governance, AWS Networking and Content Delivery, AWS Security, Identity, and Compliance, etc.

• Well-versed in Virtualization & Containerization; must demonstrate experience in technologies such as Kubernetes, Istio, Docker, OpenShift, Anthos, Oracle VirtualBox, Vagrant, etc.

• Well-versed with demonstrable working experience with API Management, API Gateway, Service Mesh, Identity & Access Management, Data Protection & Encryption.

• Hands-on experience with demonstrable working experience with DevOps tools and platforms viz., Jira, GIT, Jenkins, Code Quality & Security Plugins, Maven, Artifactory, Terraform, Ansible/Chef/Puppet, Spinnaker, etc.

• Well-versed with Storage, Networks and Storage Networking basics which will enable you to work in a Cloud environment.

•  Experience : 5+Years

• Job Location : Remote/Pune

• Extensive experience in developing Java EE application
• Hands-on experience working with Spring, Spring Boot
• In-depth knowledge of relational and NoSQL databases.
• Experience working with Java Web Services, RESTful services 
• Experience using Redis, Memcached or any other caching system
• Experience working with message brokers– preferably RabbitMQ
• Experience with infrastructure automation technologies like Docker, Kubernetes.
• Experience with build automation technologies like Maven, Gradle.

Candidates should have worked with Startups (IT Product Firms)

Should be from B2C Firms/Product/SaaS Firms

Key Skills: Python, Golang, Java, Distributed Systems, Cloud, Microservices Architecture, MVC, Design Patterns, Data Structure, Algorithms

Your Experience Across The Years in the Roles You’ve Played

• 6+ years of technology experience (at least 2 years in direct engineering management)
• Managing a 5-15 member engineering team in an agile product org
• Track record of collaborative working with multiple stakeholders
• Planning and analysis with effective communication skills

You’ll Be Improving & Responsible For

• Our products engineering team that works on initiatives fuelling the growth of our recent health retail insurance products
• Collaboration across cross-functional stakeholders to ensure delivery timelines are met
• Implementing product engineering best practices, and evangelizing them within the org
• Engineering management with a strong sense of ownership
• Problem solving with a clear and analytical approach and organized work habits
• Technological innovation in agile product engineering scenarios
• Product and business management principles and metrics