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AI Engineer - LLM / Python

AI Engineer - LLM / Python

AgileWatersPune
5 days ago
Job description

Job Description :

Key Responsibilities :

  • Design, develop, and deploy AI / ML models and pipelines to support product features and internal automation needs.
  • Build and integrate agentic workflows that allow AI agents to operate across multiple systems, take actions, and orchestrate end-to-end processes within our SaaS platform.
  • Leverage AWS Bedrock and other cloud-native AI platforms to deploy and scale LLMs in production environments.
  • Work closely with product managers, engineers, and business analysts to translate customer workflows into AI-powered solutions.
  • Fine-tune and optimize LLMs and other generative AI models for domain-specific use cases in behavioral healthcare.
  • Develop AI agents and services that improve efficiency in documentation, claims, credentialing, and patient management workflows.
  • Collaborate with data engineering teams to ensure high-quality, structured datasets for training and evaluation.
  • Evaluate, benchmark, and integrate third-party AI APIs and tools where beneficial.
  • Monitor model performance in production, ensuring reliability, scalability, and compliance with US healthcare requirements.
  • Implement guardrails, prompt engineering techniques, and responsible AI practices to deliver safe, accurate, and explainable outputs.
  • Partner with QA and DevOps to ensure robust testing, deployment, and monitoring of AI features
  • Stay updated on the latest advancements in AI / ML and proactively suggest applications relevant to healthcare SaaS.

Requirements :

  • 4+ years of experience in AI / ML engineering, with at least 2+ years hands-on experience deploying models in production environments.
  • Strong programming skills in Python and familiarity with frameworks like PyTorch, LangChain or Experience building AI agentic workflows (multi-step reasoning, tool use, action execution) in real-world applications.
  • Hands-on experience with AWS Bedrock, SageMaker, or other cloud-native AI / ML services.
  • Experience with fine-tuning and deploying large language models (LLMs) or generative AI solutions.
  • Solid understanding of NLP, information retrieval, embeddings, and prompt engineering.
  • Experience working in enterprise SaaS environments; familiarity with healthcare or insurance domains is a strong plus.
  • Understanding of data engineering concepts (ETL pipelines, SQL / NoSQL databases, APIs, cloud data storage).
  • Ability to balance research and experimentation with pragmatic product-driven implementation.
  • Excellent problem-solving skills and strong collaboration across cross-functional, globally distributed teams.
  • (ref : hirist.tech)

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