Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration.
Key Responsibilities:
- Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines.
- Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions.
- Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives.
- Translate business needs into scalable, production-ready AI solutions.
- Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases.
- Contribute to architecture discussions, code reviews, and performance optimization.
Skills Required:
- Proficient in Python, Langchain, and SQL.
- Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows.
- Background in machine learning or software engineering with a focus on system-level thinking.
- Experience working with cloud platforms like AWS, Azure, or GCP.
- Ability to work independently while collaborating effectively across teams.
- Excellent communication and stakeholder management skills.
Preferred Qualifications:
- 1+ years of hands-on experience in LLMs and Generative AI techniques.
- Experience contributing to ML/AI product pipelines or end-to-end deployments.
- Familiarity with MLOps and scalable deployment patterns for AI models.
- Prior exposure to client-facing projects or cross-functional AI teams.
