AVP, GenAI Enterprise Architect
At a glance
Mid-level AI Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Design full generative AI systems, including retrieval-based generation and vector data components
- Compare commercial and open-source models, then tune selections for specific domain needs
- Set up LLMOps practices for version control, evaluation, prompt handling and continuous delivery
- Connect AI systems to APIs, applications and databases while applying security and safeguards against false or hostile outputs
- Translate business problems into AI plans with stakeholders and create governance frameworks
What you bring
- A bachelor’s or master’s degree in computer science, AI, data science or a related discipline
- Eight to fifteen years working in software engineering, machine learning or AI
- Experience building or working with enterprise-scale systems
Who this fits
This role suits an experienced AI or software professional who can combine system architecture with model selection, production operations and security. It is a hybrid position based in Gurugram, India.
From the employer
Role Overview: Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by
selecting appropriate models, building data pipelines, and integrating them with cloud platforms
(AWS, Azure, GCP). Lead technical strategies, ensure scalability, manage AI security/
hallucinations, and bridge business needs with engineering teams.
Key Responsibilities
System Design & Architecture: Architect end-to-end Generative AI systems, including
retrieval-augmented generation (RAG) and vector data systems.
Model Selection & Tuning: Evaluate and select cutting-edge commercial (e.g., GPT-4) and
open-source models, and fine-tune models for domain-specific use cases.
LLMOps & Pipelines: Establish LLMOps standards for model versioning, evaluation, prompt
management, and CI/CD, ensuring robust, production-grade AI.
Integration & Security: Integrate AI solutions with existing APIs, applications, and databases
while enforcing security, privacy, and guardrails to manage hallucinations and adversarial
attacks.
Strategic Leadership: Collaborate with stakeholders to map business challenges to AI
solutions and establish AI governance frameworks.
Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field;
8–15 years in software engineering, ML, or AI roles. Experience with enterprise-level systems.