AI Engineer

Role Overview We are looking for a AI Engineer to join our project delivery team and build cutting-edge GenAI-powered solutions. This role focuses on designing, developing, and deploying applications powered by Large Language Models (LLMs) and modern AI systems. The ideal candidate will have hands-on experience with GenAI frameworks, prompt engineering, and integrating AI into scalable applications.

You will work on enterprise-grade AI use cases, solving real-world problems using advanced AI techniques in an agile environment.

Key Responsibilities

GenAI Development & Implementation Design and develop applications using Large Language Models (LLMs) and GenAI frameworks. Develop prompt engineering strategies to improve accuracy, relevance, and performance of LLM outputs. Work on AI use cases such as chatbots, document processing, summarization, and knowledge assistants.

Implement data preprocessing, chunking, and embedding workflows for unstructured data. Integrate GenAI models into APIs, microservices, or enterprise applications. Monitor, debug, and improve model responses, latency, and cost efficiency. Collaboration & Delivery Collaborate with product managers, engineers, and stakeholders to translate business requirements into GenAI solutions.

Participate in sprint planning, stand-ups, and design/code reviews. Work closely with data engineering and DevOps teams for scalable deployments. Ensure smooth integration of GenAI components into production systems. Evaluation, Testing & Governance Define and implement evaluation metrics for LLM outputs (accuracy, hallucination, relevance).

Conduct testing, validation, and iterative improvements to GenAI pipelines. Document prompts, workflows, and system design decisions. Ensure responsible AI practices, including data privacy and safe AI usage.

Requirements

Required Skills & Experience 2+ years of experience in AI/ML, with strong exposure to Generative AI systems. Proficiency in: Programming: Python GenAI/LLM Tools: OpenAI / Azure OpenAI / similar APIs Data Handling: Working with structured & unstructured data Frameworks: Langchain, LangGraph, LlamaIndex, etc. Experience in designing AI solutions using modular coding practices Experience building RAG pipelines and working with vector databases and RAG Evaluations.

Strong understanding of prompt engineering, vector embedding, and context management. Experience integrating AI solutions via REST APIs. Familiarity with Docker, CI/CD pipelines, and cloud platforms (Azure).

Preferred Qualifications

Bachelor's or master's degree in computer science, AI, Data Science, or related field. Experience with: Fine-tuning or adapting LLMs Multi-agent systems or tool-augmented LLMs Knowledge graphs or semantic search Exposure of enterprise-scale AI applications or production deployments. Soft Skills Strong analytical and problem-solving abilities.

Effective communication and collaboration skills. Ability to work in a fast-paced, agile environment. Proactive mindset with a focus on ownership and delivery. Eagerness to learn and experiment with emerging GenAI technologies.

Benefits

Opportunity to work with a dynamic and fast-paced engineering IT organization. Be part of a company that is passionate about transforming product development with technology.