AI Engineer Agent Development

Job Title: AI Engineer Agent Development

Location: [On-site / Remote / Hybrid]

Employment Type: [Full-time / Contract]

About the Role

We are looking for an AI Engineer specialized in agent development to design, build, and scale intelligent autonomous systems. This role will focus on LLM-powered agents, multi-step reasoning, tool integrations, and orchestration frameworks that allow AI systems to interact with APIs, data sources, and humans.

You will be at the forefront of shaping how generative AI is applied in production — developing robust, safe, and scalable agentic architectures.

Key Responsibilities

Design, develop, and deploy AI agents capable of autonomous reasoning, planning, and multi-step task execution.

Implement tool-use, API integration, memory, and retrieval-augmented generation (RAG) within agents.

Develop workflows for multi-agent collaboration, delegation, and orchestration.

Fine-tune and optimize LLMs and agent frameworks (e.g., LangChain, LlamaIndex, Haystack, Semantic Kernel, custom implementations).

Research and apply methods for reflection, error recovery, and self-correction in agents.

Integrate agents into production environments, ensuring scalability, security, and observability.

Work closely with product teams to design use cases (copilots, task automation, reasoning systems, etc.).

Stay updated with emerging approaches in autonomous AI, multi-modal agents, and reinforcement learning for LLMs.

Required Qualifications

Bachelor’s/Master’s in Computer Science, AI, Data Science, or related field.

Strong programming experience in Python (TypeScript/Go a plus).

Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, AutoGen, Semantic Kernel).

Knowledge of retrieval-augmented generation (RAG), vector databases (Pinecone, Weaviate, Milvus, FAISS).

Experience with prompt engineering, fine-tuning, and LLM APIs (OpenAI, Anthropic, Mistral, LLaMA, etc.).

Familiarity with MLOps for LLMs — model deployment, monitoring, evaluation, and feedback loops.

Strong problem-solving and system design skills.

Preferred / Nice-to-Have

Experience with autonomous agent frameworks (AutoGPT, BabyAGI, CrewAI, or custom).

Research or practical work on reflection, planning, and reasoning in LLMs.

Experience with multi-agent simulations, emergent behavior, or reinforcement learning.

Knowledge of safe AI practices — alignment, hallucination control, and red-teaming agents.

Open-source contributions in the agentic AI ecosystem.

What We Offer

Opportunity to lead next-generation agent development projects.

Competitive pay, benefits, and growth opportunities.

Work with a highly innovative team pushing the boundaries of generative AI.

A culture that encourages experimentation, learning, and applied research.