Senior Gen AI Engineer - 7 years - Immediate Joiners
Job Description
As a Gen AI Engineer / Sr. Gen AI Engineer, you will lead the design, development, and deployment of
production-grade AI solutions. You aren't just building prototypes; you are architecting scalable RAG
systems, fine-tuning models for specific domain expertise, and ensuring that GenAI capabilities
integrate seamlessly into enterprise-level applications.
Key Responsibilities
LLM Orchestration: Design and deploy sophisticated LLM-based applications using
frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
Model Optimization: Lead the fine-tuning of open-source and proprietary models to
improve performance, latency, and cost-efficiency.
Advanced RAG Systems: Architect and optimize Retrieval-Augmented Generation (RAG)
pipelines utilizing vector databases like Pinecone, FAISS, Weaviate, or Azure AI Search.
Scalable Deployment: Containerize services using Docker and deploy via FastAPI and Azure
Functions to ensure high availability and low latency.
Productization: Build and scale enterprise-grade chatbots, copilots, and automated content
generation tools using OpenAI/Azure OpenAI and Hugging Face.
Prompt Engineering: Implement and manage advanced prompt optimization and versioning
workflows to enhance model accuracy.
Monitoring & Evaluation: Establish robust evaluation frameworks (e.g., RAGAS, TruLens) to
track model performance, hallucination rates, and drift in production.
Operationalization: Collaborate with cross-functional teams (Product, DevOps, Data) to
identify high-impact use cases and move them from POC to production.
Best Practices: Set the standard for GenAI engineering, including model selection criteria,
performance tracking, and ethical AI safeguards.
Required Skills & Qualifications
Overall Experience: 3 to 6 years of professional software engineering experience.
GenAI Domain Experience: 2 years of dedicated, hands-on experience building GenAI, LLM,
and OCR solutions in production environments.
Programming Mastery: Deep proficiency in Python with expertise in asynchronous
programming, typing standards, and clean code principles.
Generative AI & LLMs: Hands-on experience with commercial APIs ( OpenAI GPT-4o,
Anthropic Claude, Azure OpenAI ) and open-source models ( Llama 3, Mistral ), along with
modern agentic frameworks.
Vector Infrastructure & Search: Practical experience with hybrid search (dense + sparse),
re-ranking algorithms, metadata filtering, and vector index tuning.
Backend & Cloud: Strong background in FastAPI, Docker, Git, CI/CD pipelines , and enterprise
cloud ecosystems ( Azure / AWS ).
Problem Solving: Proven track record of solving hallucination, context window limitations,
and data grounding issues in production.