Specialist - Product Engineering
LTIMindtree · IT Services & Consulting
- Pune, India
- On-site
- Posted today
- Software Engineering
About the job
Job Title: Specialist - Product Engineering
Location: Pune
Experience: 5-8 years
We are seeking a highly skilled Specialist - Product Engineering to join our innovative team in Pune. This role focuses on the design, development, and deployment of cutting-edge Generative AI solutions, particularly those leveraging Large Language Models (LLMs) to drive product innovation. The ideal candidate will possess deep expertise in GenAI and LLMOps, coupled with strong Python programming skills.
Job Description:
Design and develop advanced LLM-powered agents and sophisticated AI workflows.
Construct and optimize Retrieval Augmented Generation (RAG) pipelines utilizing embeddings and vector databases.
Engineer advanced prompts, including few-shot learning, structured output generation, and effective tool calling mechanisms.
Implement robust text-to-SQL and insight generation pipelines to extract actionable intelligence from data.
Develop and apply comprehensive evaluation frameworks to assess the accuracy, latency, and cost-efficiency of AI models.
Collaborate closely with backend engineering teams to ensure seamless productionization and deployment of AI systems.
Conduct thorough debugging and experimentation to continuously improve model performance and reliability.
Stay abreast of the latest advancements in GenAI and LLMOps to integrate cutting-edge solutions into product development.
Contribute to the architectural design and technical strategy for AI product development initiatives.
Skills and Qualifications:
5-8 years of professional experience in product engineering or a related AI/ML role.
Proven expertise in Python programming for AI/ML development.
Demonstrated hands-on experience with large language model (LLM) APIs, such as OpenAI or Anthropic.
Proficiency in LLM orchestration frameworks like LangChain, LlamaIndex, or equivalent.
Solid understanding of embeddings, semantic search, and Retrieval Augmented Generation (RAG) architectures.
A strong aptitude for debugging, problem-solving, and experimental design in AI contexts.
Preferred Qualifications:
Experience with MLOps/LLMOps platforms and tools (e.g., MLflow, Langfuse, Weights & Biases).
Familiarity with multi-agent system design and implementation.
Domain knowledge in analytics or pharmaceutical industries.
Understanding of cost optimization and model routing strategies for AI deployments.