Lead AI Engineer - Generative AI & Agentic AI: Cogentiq
Fractal (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 35–60 LPA
Posted 14h ago
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Job description
Structured overview of role & requirements
About This Role
- Architect, develop, and productionize enterprise-scale Generative AI and AI/ML solutions across use cases involving LLM-powered applications, RAG, AI agents, and multi-agent workflows.
- Design scalable AI services, backend applications, and APIs using Python; integrate AI capabilities with Snowflake, enterprise data platforms, and cloud ecosystems.
- Lead technical design decisions, establish AI engineering best practices (evaluation, observability, security, guardrails), mentor engineers, and drive deployment to scalable production-grade systems.
Minimum Requirements
- 10+ years of experience in software engineering, AI/ML, or related tech roles with recent hands-on experience building production-grade AI/GenAI solutions.
- Strong proficiency in Python, software engineering, system design, and building/deploying LLM/Generative AI applications beyond PoCs.
- Experience with RAG, prompt engineering, embeddings, vector search, agentic AI, and major LLM ecosystems (OpenAI, Azure OpenAI, Anthropic, Google Gemini).
- Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science, or related technical discipline.
Ideal Candidate Profile
- Has personally architected and built scalable, secure production GenAI systems integrating enterprise data and applications.
- Demonstrates expertise in designing production RAG and Agentic AI architectures, and optimizing latency, cost, security, and observability.
- Experienced in leading engineering teams, driving AI technical leadership, and collaborating across product, data science, and architecture stakeholders.