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
.
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
.
prompt engineering, vector embedding, and context management
.
- Experience integrating AI solutions via
REST APIs
.
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.
