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Senior AI Engineer

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Hybrid

Senior AI Engineer

Quess IT Solutions

Senior AI Engineer

Skills

DockerPythonPostgreSQLMachine LearningAIKubernetes

1 month ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Hybrid

Published on:

29 September 2026

What they need


Job Title: AI Software Architect / Senior AI Engineer (LLM & Agentic Systems)

Qualifications

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or related field.
  • 10+ years of software engineering experience with at least 5 years focused on LLM-based solutions and generative AI systems.
  • Demonstrated experience designing and deploying complex production-grade AI applications using Large Language Models.
  • Extensive experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or equivalent technologies.
  • Hands-on experience implementing AI observability and evaluation frameworks using Langfuse, LangSmith, or similar platforms.
  • Proven expertise with Retrieval-Augmented Generation (RAG) architectures and vector database technologies.
  • Strong understanding of modern LLM architectures, prompting strategies, context management, embeddings, and retrieval techniques.
  • Strong Python development experience and software engineering fundamentals.
  • Experience designing scalable APIs and cloud-native architectures.
  • Ability to evaluate architectural trade-offs involving model performance, latency, reliability, maintainability, and cost.
  • Experience deploying AI solutions in production environments using Docker, Kubernetes, and cloud platforms.
  • Strong understanding of structured and unstructured data processing pipelines.
  • Familiarity with modern database technologies including PostgreSQL, vector databases, and document stores.
  • Excellent communication, leadership, and mentoring skills and ability to collaborate effectively with cross-functional teams.\

Preferred Skills

  • Experience building agentic systems involving tool use, planning, memory, and multi-agent orchestration and skills.
  • Experience with model evaluation, benchmarking, AI testing frameworks, and automated quality assessment.
  • Experience working with multiple commercial and open-source models including OpenAI, Anthropic, Gemini, Llama, and Mistral.
  • Familiarity with fine-tuning, synthetic data generation, and model optimization techniques.
  • Familiarity with developing and training machine learning models.
  • Experience supporting AI products in regulated, privacy-sensitive, or high-availability environments.
  • Experience integrating AI capabilities into mobile and web applications.
  • Familiarity with modern software delivery practices including DevOps, CI/CD, and Agile development methodologies.

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