Job Description

Design, develop, troubleshoot and debug software programs for databases, applications, tools, networks etc.

Technical Expertise:

Qualification & Experience:

Bachelor's or Master's degree in Computer Science, Engineering, or related technical field. Minimum 3+ years' hands-on experience in software development using Java, Python, Spring Boot, with strong grounding in data structures, algorithms, and their application in solving complex engineering challenges.

Application Development:

Experience in designing, scalable microservices in an enterprise environment.

Self-Sufficiency:

Proven ability to rapidly learn new technologies, prototype solutions, and independently design and implement application components.

LLM Technologies:

Practical exposure to working with Large Language Models (OpenAI, Grok, or open-source variants), including prompt engineering practices, fine-tuning methods, and model deployment strategies.

Agentic Frameworks:

Hands-on development of agent-based workflows using frameworks such as OpenAI Agent SDK, LangGraph, or equivalent agent orchestration toolsets.

RAG Systems:

Experience implementing Retrieval-Augmented Generation components including indexing, metadata strategies, hybrid search, relevance evaluation, and pipeline integration.

Preferred Qualifications

OCI Services:

Experience with Oracle Cloud Infrastructure, including services such as OCI GenAI Service, Object Storage, API Gateway, Functions, or Streaming.

Containers:

Hands-on familiarity with Kubernetes on Oracle Kubernetes Engine (OKE) and container tooling such as Podman or Docker.

Vector Data Platforms:

Familiarity with vector-enabled data systems such as Oracle 23ai Vector Database, Pinecone, FAISS, or comparable technologies (desirable).

Soft Skills & Leadership

Proven ability to drive technical outcomes, take ownership of deliverables, and work independently in fast-evolving AI solution spaces. Strong communication skills, with the ability to articulate technical concepts, document solution approaches, and collaborate across distributed teams. Demonstrated problem-solving ability when working with complex AI workloads, distributed systems, and cloud-native application behaviours. A proactive, experimentation-oriented mindset with a strong willingness to learn emerging AI technologies, frameworks, and engineering patterns.

Key Responsibilities

Cloud Application Development

Design and develop cloud-native application services on Kubernetes using Java, Python, and Spring Boot. Integrate application components with OCI services, including GenAI Service, Object Storage, and API Gateway.

AI, LLMs, and Agentic Systems

Implement AI-powered capabilities using LLMs, prompt engineering, and agentic frameworks such as OpenAI Agent SDK or LangGraph. Build RAG workflows including embeddings, indexing, and hybrid search.

DevOps and Deployment

Support CI/CD processes and containerized deployment workflows using Podman, Docker, and OKE. Troubleshoot application and runtime issues across distributed environments.

Collaboration and Knowledge Sharing

Work with cross-functional engineering teams to align solution designs with business requirements. Conduct independent research on emerging AI technologies, tools, and engineering patterns to introduce improvements and new solution approaches. * Share knowledge, mentor peers, and contribute to internal enablement of AI and cloud development best practices.