Applied AI Agents Engineer

Job Summary:
We are seeking an Applied AI Agents Engineer with a strong software engineering background to design, implement, and deploy intelligent agent-based systems powered by large language models (LLMs), retrieval-augmented generation (RAG), and orchestration frameworks like LangChain.
The ideal candidate will have 3–5+ years of software engineering experience and at least 1–2 years working in AI/ML or intelligent systems. You will play a key role in building multi-agent workflows, integrating agents into enterprise environments, and deploying them reliably in production.
Experience with orchestration platforms (e.g., aiXplain) and prompt engineering will be highly valuable.

Key Responsibilities:

• Agent Development & Architecture – Design and implement AI agents using LangChain, including reasoning, memory, RAG pipelines, and tool integrations.
• Integration & APIs – Build connectors for databases, APIs, and enterprise systems to extend agent capabilities.
• Scalability & Deployment – Deploy agents to cloud environments, ensuring reliability, security, and performance optimization.
• Optimization & Monitoring – Fine-tune prompts, optimize retrieval workflows, and monitor system performance.
• Collaboration & Documentation – Work closely with AI specialists, data engineers, and domain experts to align solutions with business needs.

Requirements:
Required Skills & Experience:

• Strong foundation in software engineering (data structures, algorithms, distributed systems, OOP).
• Proficiency in Python with solid experience in LangChain (agents, chains, RAG pipelines, tool integrations).
• Good understanding of LLMs, embeddings, and vector databases.
• 3–5+ years of professional software engineering experience.
• 1–2+ years working in AI/ML or intelligent systems.

Nice-to-Haves (Plus):

• Hands-on experience with aiXplain for agent deployment, orchestration, and monitoring.
• Familiarity with prompt engineering and evaluation frameworks.
• Experience building and scaling multi-agent collaboration systems.