AI Engineer

We are looking for a talented AI Engineer with 4-8 years of experience to design, develop, and deploy AI/ML solutions for real-world business problems. The ideal candidate should have strong hands-on experience in Machine Learning, Generative AI/LLMs, Python, and production-grade AI systems. You will work closely with product, engineering, and data teams to build scalable AI solutions and take models from experimentation to production.

Responsibilities:

• Design, develop, train, evaluate, and deploy machine learning and AI models.
• Build and integrate Generative AI and LLM-based applications into production systems.
• Develop AI pipelines covering data preparation, model development, evaluation, deployment, and monitoring.
• Work with LLMs, RAG, embeddings, vector databases, prompt engineering, and AI agents.
• Fine-tune and optimise models based on business and product requirements.
• Build scalable APIs and AI services using Python and frameworks such as FastAPI/Flask.
• Implement model evaluation, observability, performance monitoring, and continuous improvement.
• Collaborate with Data Scientists, Software Engineers, Product Managers, and other stakeholders.
• Optimise AI solutions for accuracy, latency, scalability, and cost.
• Stay updated with emerging developments in Generative AI, LLMs, ML frameworks, and AI infrastructure.

Requirements:

• 4-8 years of hands-on experience in AI/ML Engineering or a related role.
• Strong programming skills in Python.
• Strong understanding of Machine Learning and Deep Learning concepts.
• Hands-on experience with Generative AI / LLMs.
• Experience with RAG pipelines, vector databases, embeddings, and prompt engineering.
• Experience with frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex or equivalent.
• Experience building and deploying production-grade AI/ML applications.
• Good understanding of REST APIs, microservices, and cloud-based deployments.
• Experience with databases such as PostgreSQL, MongoDB, or similar.
• Familiarity with Docker, Kubernetes, CI/CD, and MLOps is preferred.
• Strong problem-solving and analytical skills.

Good to Have:

• Experience with AI Agents / Agentic AI.
• Experience working with OpenAI, Gemini, Claude, Llama, Mistral, or other foundation models.
• Experience with model fine-tuning, LoRA/QLoRA, or other parameter-efficient fine-tuning techniques.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of distributed systems and scalable AI architectures.
• Experience with AI evaluation frameworks and LLM observability tools.
• Strong hands-on engineering mindset.
• Ability to take AI solutions from POC to production.
• Strong understanding of software engineering best practices.
• Ability to work in a fast-paced, collaborative environment.
• Passion for building practical and scalable AI solutions.