AI Developer

Job Title: AI Developer

Level: Mid & Senior

Location: Urla, Izmir

Type: On-site

About Efsora

We are a fast-growing software and AI development company that partners with innovative enterprises and scaleups to deliver large, cutting-edge R&D projects.

Our teams work as extensions of our clients’ internal R&D, combining advanced technology expertise, AI-centric engineering, and agile development to build impactful solutions.

We focus on augmenting our clients’ R&D capabilities, accelerating innovation, and managing technical risks from early-stage prototyping to full-scale deployment.

As part of our team, you’ll work on exciting, high-stakes projects that shape the future of industries, collaborate with top-tier talent, and grow your skills at the frontier of AI and software development.

The Opportunity

We are seeking a talented and experienced AI Developer with a strong focus on LLMs and agentic architectures to join our team.

You will play a pivotal role in designing, developing, and deploying cutting-edge, goal-oriented AI solutions that will enable automated problem-solving, create adaptive user experiences, and drive autonomous operational efficiency — to name just a few key use cases.

What You'll Do

• Lead the design and implementation of agentic architectures and autonomous AI systems leveraging Large Language Models (LLMs) as core reasoning and interaction components.
• Develop strategies for LLM-powered planning, memory management, tool integration, and multi-step reasoning.
• Architect and build robust orchestration layers that enable LLMs to interact with external APIs, databases, and other systems to achieve complex goals.
• Design, develop, and maintain backend services and APIs that power our AI applications, ensuring scalability, performance, and security.
• Design and implement specialized techniques for prompt engineering, few-shot learning, in-context learning, and fine-tuning to optimize LLM performance within agentic workflows.
• Develop robust evaluation metrics and methodologies for agent performance, focusing on task completion, efficiency, robustness, and failure modes.
• Collaborate closely with product managers and other AI & software developers to understand complex business requirements and translate them into practical, autonomous AI solutions.
• Deploy and maintain sophisticated LLM-based agentic applications in production environments, ensuring their reliability, efficiency, and continuous improvement, including monitoring, cost optimization, and safety mechanisms.
• Stay up-to-date with the latest advancements in LLM research, NLP, AI agents, reinforcement learning, and MLOps, bringing new ideas and approaches to the team.
• Participate in code reviews, technical discussions, and contribute to the overall architecture and design of our intelligent agent systems.

What We're Looking For:

Experience:

• 3+ years of professional experience in developing and deploying AI/ML models, with a significant portion focused on NLP/NLG and demonstrable experience with agentic systems.

LLM Proficiency:

• Deep practical experience with Large Language Models, including:
• Advanced use and fine-tuning of models from libraries like Hugging Face Transformers
• Extensive experience with LLM APIs (e.g., OpenAI GPT, Anthropic Claude, Google Gemini)
• Expertise in prompt engineering, few-shot learning, and in-context learning

Agentic System Design:

• Experience in designing and implementing agentic architectures, including concepts like:
• Planning and reasoning loops
• Memory management (short-term and long-term)
• Tool/function calling and integration
• Multi-agent systems

Programming:

• Strong proficiency in Python and relevant AI/ML/NLP libraries (e.g., PyTorch, TensorFlow, Keras, spaCy, NLTK)

Problem-Solving:

• Exceptional analytical and problem-solving skills, with the ability to architect and debug complex, interdependent AI systems

Collaboration:

• Strong communication and collaboration skills, with the ability to lead technical discussions and work effectively in a team environment

Bonus Points If You Have

• Direct experience with agent orchestration frameworks (e.g., LangGraph, LlamaIndex, AutoGen)
• Understanding of Reinforcement Learning from Human Feedback (RLHF) and its applications in agentic training
• Experience with control flow and state management in complex AI systems
• Experience with Model Context Protocol (MCP)
• Experience with Streamlit, Gradio, or Dash for rapid prototyping and deployment of AI/ML demos and applications
• MLOps experience, especially in deploying and monitoring complex, stateful agentic systems in production on cloud platforms (AWS, Azure, GCP), including containerization (Docker) and orchestration (Kubernetes)
• Familiarity with CI/CD pipelines for full-stack deployments
• Contributions to open-source projects or a strong GitHub profile
• Experience in a startup or fast-paced environment