Full Stack Java Technical Specialist - React.js

Job Summary

We are seeking a Forward Deployment AI Engineer to join our innovation team focused on leveraging modern technologies, including Generative AI, to accelerate software development and deliver impactful solutions.
In this role, you will work across the full stack, build prototypes and production-ready applications, and contribute to the design and implementation of AI-driven capabilities, including LLM-based solutions.
You will collaborate with cross-functional teams to evaluate emerging technologies and translate ideas into scalable solutions that improve engineering productivity and business outcomes.

Key Responsibilities

Design, develop, and deploy end-to-end AI-powered applications across frontend, backend, and AI layers
Build and integrate LLM-based solutions, including RAG pipelines and prompt engineering workflows
Develop and consume REST APIs and implement seamless system integrations
Build full-stack applications using modern frameworks (Python, Node.js, Angular/TypeScript)
Design and manage data pipelines (ETL/ELT) and work with relational, NoSQL, and graph databases
Deploy and manage applications in cloud environments (AWS/Azure/GCP) using core cloud services
Ensure scalability, performance, and reliability of applications through effective system design
Implement monitoring, logging, and evaluation mechanisms for AI and application performance
Collaborate with business and technical stakeholders to translate requirements into technical solutions
Contribute to rapid prototyping, innovation initiatives, and continuous improvement of engineering practices

Skill Requirements

Programming & Software Engineering (Required)

Strong proficiency in Python (primary language)

Experience in JavaScript / TypeScript:

Backend frameworks: Node.js / Angular
Exposure to Java or .NET ecosystems

Strong experience in SQL / NoSQL databases:

Experience with Graph Databases (Neo4j, Cypher)

Full-Stack & Integration:

API development and consumption (REST services)
Frontend development (Angular / TypeScript)
Data integration: APIs, workflows, and data orchestration
Experience with data pipelines (ETL/ELT)

Cloud & DevOps (Hands-on Delivery Focus)
Experience with at least one cloud: AWS / Azure / GCP
Hands-on usage of core cloud services (compute, serverless, NoSQL, etc.)

AI / ML Specialization (Critical Requirement)
Strong understanding of LLM fundamentals (transformers, prompting)
Hands-on experience building RAG pipelines end-to-end

Other Requirements

Good to Have:

Containers (Docker) and orchestration (Kubernetes)
Infrastructure as Code (Terraform)
Observability tools (Splunk, Open Telemetry, tracing)
Vector databases (Pinecone, Weaviate, PGVector)
Frameworks: Lang Chain, Lang Graph, Llama Index, CrewAI
AI evaluation, guardrails, and observability
MLOps fundamentals (deployment, monitoring, versioning)

Responsible AI practices:

Experience with Prompt Engineering:

Familiarity with AI coding assistants (GitHub Copilot, Codex)
Exposure to mainframe / COBOL environments
Participation in GenAI hackathons or rapid prototyping initiatives
Understanding of basic distributed systems (Spark or equivalents)