Senior AI Application Engineer

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.

Career Level - IC3