Lead GenAI Engineer

Ascendion

Bengaluru

On-site

INR 3,500,000 - 7,000,000

Full time

14 days+
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Job summary

Ascendion is seeking a Lead GenAI Engineer in Bengaluru to drive architecture, design, and delivery of enterprise-scale GenAI platforms. The role demands leadership and a track record of production-grade AI systems end-to-end.

You will shape RAG and agentic workflows, scale vector retrieval, and guide LangChain/LangGraph adoption while mentoring teams and aligning AI work with business goals.

Qualifications

  • Must have 7+ years of hands-on GenAI/AI engineering experience.
  • Experience delivering enterprise-scale GenAI platforms end-to-end.
  • Proven ability to lead architecture, design reviews, and implementation.

Responsibilities

  • Define architecture and technical strategy for GenAI platforms and solutions.
  • Lead design and implementation of complex RAG systems and agentic workflows.
  • Drive adoption of LangChain / LangGraph and advanced LLM orchestration frameworks.
  • Architect high-performance vector search and retrieval systems.
  • Oversee deployment strategies, including scalable cloud-native architectures.
  • Ensure reliability, observability, and governance of AI systems in production.
  • Lead and mentor engineering teams; conduct design reviews and code reviews.
  • Collaborate with stakeholders to align AI solutions with business goals.
  • Evaluate and integrate new tools, models, and frameworks in the GenAI ecosystem.

Skills

Python
RAG & LLMs at scale
LangChain / LangGraph
Vector databases
Cloud (AWS/GCP/Azure)
Kubernetes
Microservices architecture
System design & scalability

Tools

LangChain
LangGraph
LLM orchestration frameworks

Job description

Role Overview

We are hiring a

Role Overview

We are hiring a Lead GenAI Engineer with 7–10 years of experience to drive the design, architecture, and delivery of enterprise-scale GenAI platforms. This role requires strong technical leadership and proven experience in building production-grade AI systems end-to-end.

Key Responsibilities
  • Define architecture and technical strategy for GenAI platforms and solutions
  • Lead design and implementation of complex RAG systems and agentic workflows
  • Drive adoption of LangChain / LangGraph and advanced LLM orchestration frameworks
  • Architect high-performance vector search and retrieval systems
  • Oversee deployment strategies, including scalable cloud-native architectures
  • Ensure reliability, observability, and governance of AI systems in production
  • Lead and mentor engineering teams; conduct design reviews and code reviews
  • Collaborate with stakeholders to align AI solutions with business goals
  • Evaluate and integrate new tools, models, and frameworks in the GenAI ecosystem
Required Skills
  • Expert-level proficiency in Python
  • Extensive experience with RAG, LLMs, and prompt engineering at scale
  • Strong expertise in LangChain / LangGraph and agent-based architectures
  • Deep experience with Vector Databases and retrieval optimization
  • Proven track record of deploying production-grade GenAI applications
  • Strong experience with cloud (AWS/GCP/Azure), Kubernetes, and microservices architecture
  • Solid understanding of system design, scalability, and distributed systems
Preferred Qualifications
  • Experience leading GenAI/AI transformation initiatives
  • Strong knowledge of LLMOps, MLOps, and governance frameworks
  • Exposure to fine-tuning, evaluation frameworks, and guardrails
  • Prior experience in client-facing or consulting roles
Common Must-Have Across All Roles
  • Must have worked on at least one productionized AI/GenAI application
  • Should have been involved in the end-to-end lifecycle:
  • Problem definition → Data → Model → RAG → Deployment → Monitoring
  • Strong ownership mindset and ability to work in fast-paced environments
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