AI​/ML-Gen AI

Detailed Job Description
We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, and Gen AI frameworks, along with expertise in building scalable AI applications. Experience in Developing Agentic AI solutions.

Key Responsibilities:
Design and implement Generative AI models for text, image, or multimodal applications.
Develop prompt engineering strategies and embedding-based retrieval systems.
Integrate Gen AI capabilities into web applications and enterprise workflows.
Build agentic AI applications with context engineering and MCP tools.

Required Skills & Qualifications:
10+ years of hands-on experience in AI, Data science, ML, GEN AI.
Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
Strong hands on experience with RAG pipelines and vector databases
Extensive experience with Lang Chain, Lang Graph, CrewAI, multi agent orchestration
Strong MLOps / LLMOps experience with CI/CD automation
Experience across AWS (Sage Maker, Lambda, EKS, S3) and GCP (Vertex AI)
API & microservices development using FastAPI, REST, Docker, Kubernetes
Strong Python proficiency with PyTorch / Tensor Flow
Strong MLOps/LLMOps experience with CI/CD automation,

Extensive experience with Lang Chain, Lang Graph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, Chroma

DB, and embedding lifecycle management
Strong proficiency in Python and AI/ML frameworks (PyTorch, Tensor Flow).
Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
Knowledge and experience with vector databases and RAG technique for semantic search.
Familiarity with cloud AI services (AWS Sage Maker, Azure OpenAI, GCP Vertex AI).
Understanding of MLOps practices for scalable AI deployment.
Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid retrieval, and custom embeddings,
Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, Sage Maker Pipelines, Vertex AI Pipelines, and Git Hub Actions
Experience in using cloud-native AI systems on AWS (Sage Maker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
Experience in developing multi-agent orchestration workflows using Lang Graph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision

Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.