Senior GenAI Engineer

1 week ago


india, IN Mitra AI Full time

Key Responsibilities:

AI System Design & Development:

  • Architect, develop, and deploy large-scale Generative AI, LLM-based systems, including intelligent agents and automation workflows.

LLM Integration & Optimization:

  • Integrate and optimize large language models for reasoning, summarization, and structured content generation.
  • Apply prompt design, fine-tuning, and evaluation strategies to ensure reliable and domain-aware outputs.

Knowledge & Retrieval Systems:

  • Design and implement retrieval-augmented and context-aware AI pipelines, combining embeddings, semantic search, and hybrid retrieval methods.

Backend Engineering:

  • Build robust, scalable backend services and APIs using TypeScript and Python, including real-time communication and data streaming capabilities.
  • Ensure high performance, fault tolerance, and clean integration between AI components and backend systems.

Data Pipelines & Processing:

  • Develop and manage pipelines to extract, process, and transform unstructured data (code, documents, text) into AI-ready formats.

Infrastructure & Deployment:

  • Design and maintain cloud-native, containerized, and event-driven architectures with Infrastructure-as-Code (IaC) practices.
  • Collaborate with DevOps teams to implement CI/CD, observability, and environment automation.

Model Evaluation & Monitoring:

  • Establish model evaluation metrics, continuous validation workflows, and performance dashboards to ensure production reliability and drift detection.

Leadership & Mentorship:

  • Lead design discussions, perform technical reviews, and mentor AI engineers.
  • Collaborate cross-functionally with product and platform teams to translate AI capabilities into production-grade solutions.


Required Skills

  • Strong proficiency in Python and TypeScript, with a solid background in backend or API development.
  • Proven experience in LLM-based application design, Generative AI workflows, or AI agent systems.
  • Understanding of retrieval-augmented generation (RAG) and semantic/embedding-based search principles.
  • Experience building scalable cloud-native services, including event-driven or asynchronous architectures.
  • Familiarity with infrastructure automation, container orchestration, and CI/CD pipelines.
  • Exposure to MLOps principles — model lifecycle management, evaluation, and continuous improvement.
  • Strong problem-solving, analytical, and architectural reasoning skills.
  • Excellent communication, collaboration, and mentoring abilities.


Preferred Qualifications & Experiences:

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related disciplines.
  • 3+ years of professional experience in AI/ML software engineering, including 2+ years in Generative AI or LLM-based systems.
  • Previous experience leading small engineering teams or driving architectural decisions is highly preferred.


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