Ll Oefentherapie
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.
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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.
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