[Hiring] Mid GenAI Engineer @TALENT MATCHMAKERS

Role Description

We are looking for a Mid GenAI / LLM Developer to join our partner's team & help build a production-grade AI agent platform designed to integrate with enterprise engineering tools and processes in the energy industry.

The project focuses on developing a LLM-powered multi-agent infrastructure that can orchestrate tasks, interact with multiple engineering platforms, and support complex technical workflows used by engineers.

This is a hands-on engineering role focused on building real production systems, where strong engineering execution is essential.

• Work on a large-scale enterprise AI platform used in the energy industry.
• Build LLM-powered agent systems integrated with engineering platforms.
• Opportunity to work on complex integrations across multiple enterprise tools and systems.
• Collaborate in a multidisciplinary AI, infrastructure, and platform engineering team.
• Build production GenAI systems with real operational impact.
• High ownership and strong technical autonomy.
• Opportunity to grow into AI architecture or platform leadership roles.

Qualifications

• 2-3 years of experience building backend systems with Python (FastAPI, async programming, API development).
• Hands-on experience building LLM-powered applications and agent workflows using technologies such as: LangChain; LangGraph; OpenAI / Azure OpenAI APIs; Prompt engineering; Tool calling / agent orchestration.
• Experience integrating LLM-based services with external platforms, APIs, or enterprise systems.
• Strong understanding of REST APIs and system integration patterns.
• Ability to design systems that coordinate multiple services, agents, or tools within larger application ecosystems.
• Experience with Docker.
• Ability to write maintainable code with testing discipline and a production mindset.
• Willingness to collaborate in environments where other languages (such as Go) may be used.
• Fluent in English.

Requirements

• Design and implement AI agents powered by LLMs that interact with engineering tools, APIs, and internal systems.
• Build multi-agent workflows that coordinate tasks across different systems, including prompt orchestration, tool calling, task routing, and agent collaboration.
• Develop integrations with multiple engineering platforms, APIs, and services to enable agents to execute workflows across the engineering ecosystem.
• Build backend services using Python (e.g., FastAPI) that support agent execution, orchestration logic, and system integration.
• Design scalable LLM application components including prompt pipelines, agent control logic, response validation, and interaction flows.
• Enable agents to retrieve and process information from structured and unstructured data sources across enterprise systems.
• Develop APIs and connectors allowing agents to interact with internal tools, services, and engineering platforms.
• Package services using Docker and support deployment pipelines within a cloud-based infrastructure.
• Work closely with infrastructure engineers, frontend developers, cloud architects, DevOps engineers, and product stakeholders to iteratively improve the platform.

Benefits

• Experience with Go.
• Experience with LlamaIndex, Haystack, HuggingFace Transformers, LangSmith (tracing & evaluation).
• Experience working with multi-agent architectures.
• Familiarity with vector databases or semantic retrieval systems.
• Basic knowledge of Kubernetes.
• Experience integrating with complex enterprise platforms or engineering tools.
• Experience building AI-driven internal platforms or developer tools.