Applied AI Systems Developer

About the Role

We are looking for a skilled AI / ML professional to develop, implement, and optimize machine learning models and AI solutions. The role involves data analysis, model training, and integrating AI into real world applications to solve complex business problems efficiently.

The role involves data analysis, model training, and integrating AI into real world applications to solve complex business problems efficiently.

Responsibilities

Architect and implement advanced AI solutions leveraging LLMs (and other emerging architectures), embeddings, and agentic frameworks (e.G., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI).

Develop and refine Agentic AI systems focusing on planning, memory, tool utilization, and dynamic task critic execution.

Engineer and optimize prompt engineering pipelines to achieve superior accuracy and low latency across diverse applications.

Fine-tune and deploy specialized LLMs and AI copilots to transform engineering and business operations.

Collaborate with cross-functional teams to deliver production-grade solutions that create tangible value.

Stay ahead of the curve by integrating emerging GenAI research and state-of-the-art capabilities into practical, real-world systems.

Lead projects and mentor junior engineers, contributing to a culture of innovation and growth.

Qualifications

Experience : 3-8 years of hands-on ML / AI / Deep Learning experience, with a strong portfolio of real world application development.

Technical Proficiency : Advanced Python skills and extensive experience with leading AI tools and libraries (OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow).

Core Knowledge : Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.G., FAISS, Weaviate).

Prompt Engineering Mastery : Proven expertise in designing and implementing effective, reusable prompts for complex reasoning, classification, generation, and tool integration tasks across a wide variety of models including open-source solutions.

Agentic AI Acumen : Prior experience with autonomous AI agents or multi-agent orchestration is a significant advantage.

Mindset : A startup-ready attitude - agile, intellectually curious, and hands-on, thriving in fast paced, iterative environments.

Required Skills

Advanced Python skills

Experience with leading AI tools and libraries

Deep understanding of LLMs and embeddings

Expertise in prompt engineering

Experience with autonomous AI agents