GEN AI Architect

SN Required Information Details

1 Role Gen AI Architect

2 Required Technical Skill Set (MustHave) Gen AI / LLM /Agentic AI

4 Desired Experience Range 10 to 20 Yrs

5 Location of Requirement Any

6 IOU-Detail Digital-Manufacturing

Desired Competencies (Technical/Behavioral Competency)

Must-Have • Gen AI • Experience in LLMs, Embedding Models, Prompt Engineering • Knowledge of statistical programming languages like Python • Good applied statistical skills • Good knowledge of machine learning algorithms • Proficiency in handling imperfections in data & generating insights and patterns. • Experience with Data Visualization Tools • Fine tuning of LLM • Evaluation Framework (RAGAS, ROUGE, BLUE Scrore) • Autoencoding model (Encoder: ROBERTA/ BERT/ DistilBERT) • Langsmith framework • Autoregressive model (Decoder: GPT/ BLOOM/ LLama/ Mistral/ Claude/ CodeGen/ OPT/ PaLM • RAG/Multimodal Architecture using Langchain/ LlamIndex • MCP Architecture • Experience Agentic AI Framework ( Crew AI, AutoGen, LangGraph, Google AVD etc. ) • Experience in Model deployment, LLMOps, Scalability and Performance • Fine tuning of LLM • AI ML exp. • Candidate has exp. in Transformer Architecture (Encoder and decoders) • Knowledge Graph implementation (If anyone has created knowledge graph, that's good)

Good-to-Have • Excellent Communication Skills • Strong Software Engineering Background (Productionizing the models) • Hands-on experience with data science tools • Problem-solving aptitude • Analytical mind and great business sense

SN Responsibility of / Expectations from the Role

1 • Data mining or extracting usable data from valuable data sources. • Using machine learning tools to select features, create and optimize predictive models. • Carrying out preprocessing of structured and unstructured data • Enhancing data collection procedures to include all relevant information for developing analytic systems. • Processing, cleansing, and validating the integrity of data to be used for analysis.

• Analyzing large amounts of information to find patterns and solutions. • Developing prediction systems and machine learning algorithms • Ability to use LLMs to build GenAI powered solutions. • Presenting results in a clear manner • Propose solutions and strategies to tackle business challenges. • Collaborate with Business and IT teams. • Designing and developing machine learning and deep learning systems • Knowledge of productionizing the ML and DL applications and monitoring