Remote
Full-Time
India
About the Role
Senior LLM Engineer – GenAI / ML (Python, Langchain)
Engagement Type: Full Time/FTE
Location: India
Overall Experience: 7–12 Years
Interview Flow: Will be shared soon
Availability: Full Time Availability(8 Hrs) and 4 hours overlap with PST time zone
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.
Engagement Type: Full Time/FTE
Location: India
Overall Experience: 7–12 Years
Interview Flow: Will be shared soon
Availability: Full Time Availability(8 Hrs) and 4 hours overlap with PST time zone
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.