Architect and code sophisticated AI modules, including high-performance embedding pipelines, custom chunkers, and advanced retrieval evaluators
Lead the integration of intelligent agent services with diverse internal and external APIs and vector databases to solve complex, cross-service challenges
Stay at the bleeding edge of AI research, implementing the latest advancements in fine-tuning, RLHF, and prompt engineering frameworks like DSPy
Drive agile excellence by spearheading sprint deliveries and collaborating with cross-functional leaders to define the scope of transformative AI features
Champion code quality and team growth by performing high-level peer reviews and contributing to shared utility libraries that boost development velocity
Architect and implement modular, cloud-native microservices that integrate GenAI into our production ecosystem, ensuring our Agentic solutions are as scalable and reliable as they are intelligent
Take ownership of the production lifecycle by building robust CI/CD pipelines and using observability frameworks (like Datadog or Databricks) to monitor model health, trace agent logic, and ensure system uptime
Drive technical excellence by developing comprehensive evaluation suites—incorporating both traditional testing and modern LLM-based evals—to benchmark accuracy, safety, and performance before every release

6+ years of robust engineering experience
Python expert with a deep understanding of developing and scaling high-quality code
At least 6 months of hands-on experience building and deploying GenAI applications
Strong background in RAG frameworks, including vector databases, hybrid search, and ANN algorithms
B.Tech, M.E, M.Tech, or M.S. in Computer Science Engineering from a premier institute

Agentic Artificial Intelligence Engineer

Key skills