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AmpsTek - Generative AI Engineer - LLM

Ampstek
Multiple Locations
6 - 8 Years

Posted on: 29/08/2025

Job Description

Title : Generative AI Engineer.

Location : Pune(Onsite).

Job Type : Contract.

Job Description.

You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets.

In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises.

Required skills :


- 5+ years of professional experience in building Machine Learning models & systems.

- 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.

- Experience in driving the engineering team toward a technical roadmap.

- Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.

- Understanding of Cloud services, including Azure, GCP, or AWS.

- Excellent communication skills to effectively collaborate with business SMEs.

Roles & Responsibilities :


- Develop and optimize LLM-based solutions : Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.

- Codebase ownership : Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.

- Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.

- Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.

- Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

- Continuous innovation : Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.


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