Job Description :
We are looking for an experienced Lead AI Platform Engineer to lead the design, development, and deployment of enterprise-grade Generative AI platforms. The ideal candidate will have deep expertise in LLM engineering, RAG architectures, agentic AI frameworks, and cloud-native AI deployments, with a proven track record of building scalable, production-ready AI systems and leading high-performing engineering teams.
Key Responsibilities :
- Lead the architecture, design, and development of enterprise-scale AI platforms powered by Large Language Models (LLMs).
- Design and implement scalable RAG (Retrieval-Augmented Generation) pipelines, vector search solutions, and AI knowledge retrieval systems.
- Build and optimize Agentic AI workflows using frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
- Develop AI-assisted automation and rule transformation pipelines for enterprise business processes.
- Drive prompt engineering, model evaluation, inference optimization, caching, and latency improvements for production AI systems.
- Design secure, scalable, and highly available AI services deployed on cloud platforms.
- Establish best practices for AI governance, model observability, monitoring, security, compliance, and responsible AI.
- Collaborate with product, engineering, data science, and business stakeholders to define AI architecture and technical roadmaps.
- Mentor engineering teams, conduct architecture reviews, and promote engineering excellence across AI initiatives.
- Evaluate emerging AI technologies, frameworks, and foundation models to continuously improve platform capabilities.
Required Skills :
- 12 - 15 years of software engineering experience, with significant experience in AI/ML and Generative AI platform development.
- Strong expertise in LLMs, Prompt Engineering, RAG, Vector Databases, and AI application architecture.
- Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar orchestration frameworks.
- Advanced proficiency in Python and AI/ML development frameworks.
- Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or similar enterprise AI platforms.
- Strong knowledge of cloud-native architectures on AWS, Azure, or Google Cloud Platform.
- Experience building scalable APIs, microservices, containerized applications, and Kubernetes-based deployments.
- Familiarity with MLOps, CI/CD pipelines, model versioning, monitoring, and AI observability.
- Strong understanding of AI security, governance, privacy, and responsible AI principles.
- Excellent leadership, stakeholder management, and technical mentoring skills.
Preferred Skills :
- Experience with fine-tuning foundation models and parameter-efficient tuning techniques.
- Knowledge of distributed systems, GPU optimization, and inference acceleration.
- Exposure to graph databases, knowledge graphs, and enterprise search platforms.
- Experience leading enterprise AI transformation programs.
Education (Mandatory) :
- Full-time B.E./B.Tech, M.Tech, MS, MCA, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related discipline.
(ref:hirist.tech)