Full Stack AI Application Engineer – Python / Java | Generative AI, RAG & Agentic AI

? Location: India / Remote / Offshore

? Company: NForce One

? Department: Engineering – Artificial Intelligence

? Experience: 3–7 Years

? Employment Type: Full-Time / Contract

About NForce OneNForce One is a technology services and solutions company with delivery capabilities across the United States and India. We build AI-powered products, enterprise applications, accelerators, and client-specific solutions across Generative AI, Agentic AI, Quality Engineering, Data Engineering, Cloud, and Digital Transformation.

Role OverviewWe are looking for a hands-on Full Stack AI Application Engineer who is a strong software engineer first and an AI practitioner second.

You will build complete, production-ready applications end to end, combining solid Python and Java engineering with modern front-end development and Generative AI, RAG, and Agentic AI capabilities.

You will own the complete application lifecycle, including:

- Business requirements and solution design
- Backend development and database architecture
- Vector databases and AI integrations
- LLM and Agentic AI implementation
- API and front-end development
- Testing and quality engineering
- Cloud deployment and production support

This is not a research, notebook-only, or model-experimentation role. We are looking for someone who can build, deploy, and maintain real-world AI-powered applications. Key Responsibilities1. Generative AI & LLM Integration

- Design and develop AI-powered enterprise applications, assistants, copilots, intelligent search, and workflow automation solutions.
- Integrate commercial and open-source LLMs into production systems.
- Implement prompt engineering, context engineering, structured outputs, and tool/function calling.
- Build scalable and reliable AI-powered application features.

2. RAG & Agentic AI Development

- Build end-to-end RAG pipelines covering document ingestion, chunking, embeddings, and vector storage.
- Implement hybrid and semantic retrieval, metadata filtering, reranking, and context construction.
- Evaluate RAG performance and implement techniques to reduce hallucinations.
- Build Agentic AI workflows, including multi-agent systems, agent memory, planning, orchestration, supervisor agents, and human-in-the-loop flows.

3. Backend Development

- Develop backend services, REST APIs, and microservices using Python (FastAPI, Flask, Django) and Java (Spring Boot).
- Implement authentication, validation, error handling, logging, and API versioning.




- Design scalable and maintainable backend architectures.

4. Front-End Development

- Build responsive front-end applications using React or Angular.
- Integrate front-end interfaces with backend and AI services.
- Implement streaming LLM responses, chat interfaces, and authentication flows.
- Develop clean, maintainable, and user-friendly interfaces.

5. Database & Data Engineering

- Design and work with relational, NoSQL, and vector databases.
- Build efficient data access and retrieval mechanisms.
- Work with data pipelines and integrate data engineering components where required.

6. Cloud, Deployment & DevOps

- Deploy, monitor, and support applications on Azure, AWS, or GCP.
- Work with Docker, CI/CD pipelines, and observability tools.
- Ensure application reliability, scalability, and production readiness.

7. Engineering & Innovation

- Build reusable AI services, components, and accelerators.
- Evaluate emerging AI frameworks and models for adoption.
- Contribute to AI-powered automation and quality engineering initiatives such as test generation, defect triage, root cause analysis, and self-healing automation.
- Translate business requirements into technical solutions.
- Build rapid POCs and convert successful POCs into production applications.

Required Qualifications
- 3+ years of professional software development experience.
- Solid hands-on Python development experience, writing maintainable production code (not limited to notebooks).
- Hands-on Java and Spring Boot development experience.
- Proven experience designing and building REST APIs and backend services.
- Full-stack application development experience, including:
- JavaScript or TypeScript
- React or Angular
- HTML and CSS
- Strong SQL and relational database experience (PostgreSQL, MySQL, SQL Server, or Oracle).
- Hands-on Generative AI / LLM integration experience in real applications.
- Experience building or contributing to RAG-based applications.
- Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP).
- Proficiency with Git and strong software engineering fundamentals.

Preferred Qualifications




- 4–7 years of overall IT experience, including 2+ years each in Python and Java application development.
- Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or Semantic Kernel.
- Experience building and deploying AI agents in production.
- Vector database experience with Pinecone, Weaviate, ChromaDB, FAISS, pgvector, Azure AI Search, or OpenSearch.
- Experience with microservices architecture, Docker, Kubernetes, and CI/CD (Jenkins or GitHub Actions).
- Practical ML understanding, including classification, regression, clustering, feature engineering, model evaluation, and deployment using Scikit-learn, XGBoost, or Hugging Face.
- Test automation exposure with Playwright, Selenium, RestAssured, PyTest, TestNG, JUnit, or Postman.
- Data engineering exposure with PySpark, Kafka, Airflow, Azure Data Factory, AWS Glue, and ETL/ELT pipelines.
- Databricks experience, including Delta Lake, Medallion Architecture, Unity Catalog, Workflows, and Databricks SQL.
- Monitoring and observability tools such as Grafana, Prometheus, Datadog, Azure Monitor, or CloudWatch.

Nice to Have
- GraphRAG experience.
- Fine-tuning and LoRA/PEFT.
- TensorFlow, PyTorch, and MLflow.
- Terraform and infrastructure automation.
- JMeter or performance testing.
- Appium and mobile application testing.
- Next.js and front-end state management libraries.
- Component design systems.
- Multi-cloud experience.

Ideal Candidate ProfileYou are a hands-on engineer who is comfortable working with both Python and Java and can independently build the user interface as well as the backend services.

You are curious about emerging AI technologies and capable of taking a feature from initial design through development, deployment, and production support.

You should be able to troubleshoot independently, learn new frameworks quickly, and collaborate effectively with product owners, architects, QA engineers, UI developers, and client teams.

Most importantly, you enjoy building practical, production-ready AI applications rather than limiting yourself to experimentation or prototypes.

EducationBachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or a related field, or equivalent hands-on software development experience.

NForce One is an Equal Opportunity Employer. We welcome applicants from all backgrounds.

Interested candidates can apply through LinkedIn or share their profiles with our recruitment team.

📌 Full Stack AI Application Engineer (Hyderabad)
🏢 NForce One
📍 Hyderabad