Full Stack Java Developer

About the Role

We are looking for a Full Stack AI Engineer who can take an ambiguous problem and turn it into a complete, production-ready AI product.

This is a builder role.

You will work across the entire stack — AI models, agents, backend services, APIs, databases, data pipelines, frontend applications, infrastructure, and production deployment. You should be comfortable deciding what needs to be built, writing the code, deploying it, measuring whether it works, and continuously improving it.

We are not looking for someone who only builds notebooks, trains models, writes prompts, or creates architecture diagrams for another team to implement. We want engineers who ship complete products.

A typical project might involve designing an agentic workflow, building a retrieval pipeline, writing Python APIs, creating a React interface, integrating enterprise data, deploying to Kubernetes, implementing evaluations, and debugging the application in production.

The distance between an idea and working software should be measured in weeks, not quarters.

This role is based in Hyderabad and is 6 days per week in the office.

We are looking for:

1. A person that can smoothly navigate extreme ambiguity
2. Full stack software builder
3. AI depth, must have built a production AI system
4. Excellent top-notch communication and stakeholder management
5. Prioritizes growth over work-life balance

What You'll Do

Build AI Products End-to-End

• Own AI applications from problem definition through architecture, development, deployment, and production operation.
• Translate ambiguous product and business requirements into working software.
• Build across AI/ML, backend services, APIs, databases, frontend interfaces, data pipelines, authentication, infrastructure, and observability.
• Rapidly prototype, test with real users and data, and turn successful ideas into production-grade systems.
• Make pragmatic engineering decisions based on speed, reliability, simplicity, maintainability, and user value.

AI, LLMs & Agents

• Build production applications using commercial and open-source foundation models.
• Design RAG systems, agentic workflows, tool/function calling, structured outputs, memory, human-in-the-loop workflows, and multi-agent systems where appropriate.
• Work with frameworks such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, or equivalent tools.
• Build retrieval systems using embeddings, vector search, BM25, hybrid retrieval, reranking, metadata filtering, and knowledge graphs.
• Design prompt and context engineering strategies for complex workflows.
• Evaluate model choices based on accuracy, latency, reliability, security, and cost.
• Build automated evaluations and regression tests for AI behavior.
• Fine-tune or adapt models when prompting and retrieval are insufficient.

Backend, Frontend & Data

• Build production backend systems primarily in Python using FastAPI, Flask, Django, or similar frameworks.
• Design APIs, asynchronous workflows, background jobs, queues, caching layers, and event-driven systems.
• Work with PostgreSQL, SQL Server, MongoDB, Redis, Snowflake, and other production data stores.
• Build modern applications using React, Next.js, TypeScript, JavaScript, or equivalent frameworks.
• Create interfaces for copilots, conversational AI, workflow automation, analytics, review queues, and operational applications.
• Implement streaming responses, real-time updates, authentication, permissions, and API integrations.
• Build ingestion and transformation pipelines for structured and unstructured enterprise data.
• Work with documents, databases, APIs, event streams, images, logs, and operational datasets.
• Maintain provenance, permissions, metadata, and traceability across enterprise information.

ML & Computer Vision

• Use classical ML or deep learning when it is better suited to the problem than an LLM.
• Build systems involving classification, forecasting, anomaly detection, ranking, recommendations, optimization, or prediction.
• Build computer-vision applications involving detection, classification, segmentation, OCR, tracking, or image/video analysis.
• Work with PyTorch, TensorFlow, Hugging Face, OpenCV, or equivalent tools.
• Understand model development, evaluation, inference, and productionization.

Deploy & Operate What You Build

• Deploy applications across AWS, Azure, GCP, on-premises, hybrid, or edge environments.
• Containerize and operate applications using Docker and Kubernetes.
• Build CI/CD pipelines, automated testing, monitoring, and observability.
• Own reliability, latency, availability, security, evaluation, cost, and scalability.
• Debug failures across application code, AI models, data, infrastructure, and integrations.
• Build retries, fallbacks, rollback mechanisms, and human intervention into critical systems.

Integrate With Enterprise Systems

• Connect AI applications to enterprise platforms, databases, APIs, and operational systems.
• Integrate with systems such as ERP, MES, PLM, CRM, data warehouses, IoT platforms, document repositories, and legacy applications.
• Work within enterprise networking, security, and data-governance constraints.
• Implement authentication, authorization, secrets management, auditability, permissions, and data isolation.
• Build AI systems capable of safely operating on sensitive enterprise data.

What You Bring

• 5+ years of software engineering experience, with meaningful experience building AI/ML-powered products. Exceptional candidates with less experience but strong demonstrated ability will be considered.
• Strong hands-on programming ability in Python.
• Experience building complete production applications rather than isolated models, notebooks, or proofs of concept.
• Strong backend fundamentals including APIs, databases, distributed systems, and application architecture.
• Experience with React, Next.js, TypeScript, JavaScript, or equivalent frontend technologies.
• Strong understanding of LLMs, RAG, agents, tool calling, embeddings, vector search, prompt/context engineering, AI evaluation, and ML fundamentals.
• Experience with SQL and production databases.
• Experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, or equivalent production infrastructure.
• Understanding of production AI concerns including reliability, latency, security, observability, evaluation, and cost.
• Strong debugging skills across the full stack.
• Ability to independently turn loosely defined requirements into working software.
• Strong product judgment, high agency, technical curiosity, and a bias toward shipping.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent demonstrated experience.

Preferred / Top-Candidate Signals

• You've independently shipped an AI application from database → backend → AI → frontend → production.
• You've built production RAG or agentic systems, not just demos.
• You've used LangGraph, LangChain, Semantic Kernel, LlamaIndex, or similar frameworks.
• You understand when not to use an LLM or agent.
• You've worked with hybrid retrieval, reranking, vector search, or knowledge graphs.
• You've built with both commercial and open-source models.
• You've deployed ML or computer-vision systems into production.
• You have experience with React/Next.js + Python/FastAPI or a comparable modern stack.
• You have experience with Kubernetes, cloud infrastructure, and production observability.
• You have integrated software with complex enterprise or industrial systems.
• Experience in manufacturing, industrial, supply chain, logistics, engineering, energy, aerospace, automotive, or other physical-world environments is a strong plus.
• You've built meaningful side projects, open-source software, startups, or substantial systems outside your assigned responsibilities.
• You have a history of turning vague ideas into shipped products.

What Makes Someone Exceptional

The strongest engineers in this role combine three abilities:

AI Engineering — Choose the right model, retrieval approach, agent architecture, evaluation method, or ML technique.

Software Engineering — Build everything around the intelligence: frontend, backend, data, APIs, infrastructure, security, integrations, and deployment.

Product Judgment — Understand what actually needs to be built and rapidly turn it into something users can use.

A typical week might involve designing an agent workflow, writing FastAPI services, building a React interface, creating a retrieval pipeline, connecting enterprise data, deploying to Kubernetes, implementing evaluations, and debugging real-world behavior.

You should not need five different teams to turn an idea into a working product. You should be able to build.

Why This Role

• Build entire products, not isolated models or prototypes.
• Own the full stack: AI, backend, frontend, data, infrastructure, and deployment.
• Ship quickly: move from idea to working software in weeks.
• Work across modern AI: LLMs, agents, RAG, ML, computer vision, optimization, and enterprise data.
• Solve real-world problems: build software used in complex operational environments.
• See your work in production: own the path from first commit to real users.
• Compensation is flexible for exceptional candidates. 

Full stack developer (react, node js)

Full stack developer (react, node js)

Full stack developer (react, node js)

Full stack developer (react, node js)

He can develop independetly website.

Stipend: INR. 5,000 to INR. 15,000 per month + Performance Bonus + Goodies for Elites

We are looking for skilled Full Stack Developer interns who can oversee the complete software development road cycle at Spacenos and work on building amazing products.

• Experience with JavaScript and ReactJs framework.
• Experience with NodeJs, Firebase and Firestore Functions.
• Candidates should have the ability to pick up new technologies quickly
• Knowledge of code versioning tools (such as Git, Mercurial, or SVN)

1. Creating and converting high-fidelity designs into code.
2. Assist with creating cross-platform UI Web components
3. Build responsive applications using front-end frameworks
4. Create Backend services for the UI and test with edge cases.

5. Test components using new technologies

Spacenos is the fastest-growing start-up which is innovating in the finance, edtech and marketing domain since 2015 and won multiple awards and recognitions from more than 40+ MNCs and Fortune 500 companies. Our Clients are based out of the U.S.A and Australia. We are funded & Supported by Government of Karnataka, Angel Investors and International Grants.

1. Apply for your CV and past work to be reviewed.
2. Receive a telephonic interview or assessment upon filling the final step form.
3. Receive offer letter if selected.

Apply soon, the earliest applicant would be preferred over the late applicants.

What you must have:

Have at least 2 years of experience with two or more development languages. Experience

working on Python is a MUST and that on JAVA is nice to have.

• Experience in building web platform with Angular 9+ (React could be an alternative) is a MUST
• Experience in building applications with containerization like Docker and Kubernetes
• Experience in writing relatively complex DB queries (preferably SQL Server, MySQL). Experience working on No-SQL DB is nice to have.

• Experience in building RESTful APIs using Python and web frameworks such as Spring MVC, Flask
• Experience in working in any of the ORM tools like SQLAlchemy, SQLObject, Storm, Django
• Skillful in writing high-quality, well-tested code
• Proficient in Object-Oriented programming
• Comfortable with Agile methodologies, such as Scrum, Kanban
• Experience in working with JavaScript frameworks (such as ag-Grid, D3) to build in-app reports is nice to have

• Key competencies required: Problem-Solving, Analytical, Collaboration, and Accountability
• An influencer by always advocating for technical excellence and innovation while being open to change when needed

• Resilient in ambiguous situations and can approach challenges from multiple perspectives
• Advantage if has a working knowledge of cloud technology such as AWS, Azure
• Efficiently utilize DevOps tools and practices to build and deploy software
• Have knowledge of Test Driven Development

About the Role:

We are looking for passionate and highly motivated Technologist who has delivered rock solid software solutions for industry leading enterprises with lean and agile teams. We are looking for an engineer with a strong technical background, thorough understanding of testing methodologies, a passion for quality, and a desire to make a positive change in our products. 

Roles & Responsibilities

• Work on FieldEZ product development
• Perform requirements analysis, design, coding, unit testing, reviewing and implementation
• Work closely with the manager to prioritize the requirements based on technical dependencies for product development
• Provide mentoring and coaching to junior team members
• Team management and customer management

Skills & Experience

• 5 to 7 years of experience in Information Technology
• Deep understanding and hands on experience in Core Java, J2EE, JavaScript, HTML, Spring, Spring Security, Spring Boot, Microservices, Hibernate, JPA, CSS3, Angular 2+, Jquery, SQL, MySQL, PostgreSQL, Scripting, Stored Procedures, Jenkins, Git
• Experience with REST APIs
• Work on Design patterns, UML Design (Any UML tool is fine), Application and DB clustering.
• Very good understanding of database (MySQL or Oracle), knowledge in query performance optimization
• Knowledge of development lifecycle, standards, approaches, utilities, and environment
• Exposure to responsive / progressive web development would be an added advantage.

Educational Qualification

B.Tech/ B.E or M.Tech/M.E (Computer Science/Information Technology/Electronics & Communication/ Information Science) , MCA from a reputed School and University.