Senior LLM Engineer

An older role: first posted 551d ago, and Turing still listed it when we checked today. Newer roles tend to fill faster. See the jobs hiring now.

What the work is

Senior LLM Engineer – GenAI / ML (Python, Langchain)

Full Time

Location: India Overall Experience: 7–12 Years

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.

Pay

See listing, fully remote. How payouts and tax work.