Sr. GenAI Engineer

Job Title: Sr. GenAI Engineer

Location:

Employment Type:

Mandatory Qualifications:

• 9–12 years of experience building

  production-grade machine learning systems

  .
• Strong hands-on expertise in

  LLMs, Prompt Engineering, RAG, and AI Agents

  .
• Advanced

  Python development

  with

  LangChain / LangGraph

  experience.
• Strong proficiency in

  SQL

  for data manipulation and pipeline building.
• Proven experience deploying

  GenAI applications on Azure, AWS, or GCP

  .
• Ability to design

  scalable, secure, and high-performance GenAI architectures

  .
• Excellent communication skills for stakeholder and cross-functional collaboration.
• Demonstrated ability to

  mentor engineers, lead projects, and drive innovation

  .

Required Experience:

• Sr. GenAI Engineer:

  8+ years of ML engineering experience.

• 1+ year of deep hands-on experience in LLMs & Generative AI

  , including:
• Prompt Engineering, RAG Architectures, Agentic Workflows.
• Expert-level skills in:

  Python, LangChain / LangGraph, SQL.

• Strong understanding of cloud services across

  Azure, AWS, or GCP

  .
• Proven ability to work directly with

  business SMEs and product stakeholders

  .

Roles & Responsibilities:

• Develop & Optimize LLM Solutions:

  Lead the design, fine-tuning, optimization, and deployment of LLM-powered solutions using advanced techniques such as prompt engineering, RAG pipelines, and agent-based systems.

• Code Ownership & Best Practices:

  Maintain high-quality, scalable, and efficient Python & SQL codebases with reusable components and performance-focused architecture.

• Cloud Deployment & CI/CD:

  Deploy and operate GenAI applications on Azure, AWS, or GCP with optimized infrastructure, monitoring, and automated CI/CD pipelines.

• Cross-Functional Collaboration:

  Work closely with product owners, business SMEs, data scientists, and engineering teams to translate business needs into scalable AI solutions.

• Mentorship & Technical Leadership:

  Guide, mentor, and upskill engineers while setting standards for ML and GenAI development.

• Continuous Innovation:

  Stay updated with the latest advancements in LLMs, multi-agent systems, and generative AI research. Propose and prototype new techniques to continuously enhance platform capabilities.