Lead - AI

SoftTech Engineers Ltd; Maharashtra; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

SoftTech Engineers Ltd. seeks an experienced AI Engineering Leader to drive architecture, development, and delivery of next-generation AI-powered Metaverse products.

You will lead end-to-end AI product development, build LLM-powered applications, and design scalable RAG systems integrated with immersive Metaverse environments. You will mentor high-performing AI engineering and data science teams, establish governance and responsible AI practices, and ensure cloud-native deployment and MLOps

Qualifications

• 6+ years in software engineering and product development.
• 3+ years in hands-on ML and AI product development.
• Proficiency with Gen AI, LLMs, and prompt engineering.
• Data governance and privacy compliance under applicable laws.
• Experience with RAG-based architectures and vector databases.
• Strong knowledge of Transformer models and DL frameworks.
• Proficiency in Python and AI ecosystems.
• Experience delivering AI products on cloud platforms (AWS, Azure, GCP).
• Experience with MLOps, CI/CD, monitoring, and deployment pipelines.
• Solid product ownership and stakeholder management skills.
• Experience leading large engineering teams delivering enterprise-scale products.

Responsibilities

• Define AI vision and roadmap for Metaverse products.
• Lead end-to-end AI product development from concept to deployment.
• Design and implement LLM-powered applications and AI agents.
• Build scalable RAG architectures with vector databases and knowledge bases.
• Develop ML/DL models for real-world business use cases.
• Lead Transformer-based model research and implementation.
• Collaborate with cross-functional teams across product, engineering, UX, and BIM/CAD/CAE.
• Establish AI governance, security, and responsible AI practices.
• Drive cloud-native deployments and MLOps practices.
• Mentor large AI engineering and data science teams.

Skills

6+ years exp

ML experience

Prompt engineering

Data governance

Gen AI / LLMs

RAG systems

Transformers

DL frameworks

NLP / semantic search

Vector databases

Python

Cloud platforms

MLOps / CI/CD

Product ownership

Leadership

Education

CS/AI degree

Tools

Vector databases

Knowledge repositories

MLOps tooling

Job description

Role Overview

We are seeking an experienced AI Engineering Leader to drive the architecture, development, and delivery of next-generation AI-powered Metaverse products. The ideal candidate will have deep expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Machine Learning, Deep Learning, Transformers, and AI product development. The role requires strong technical leadership, product ownership, and the ability to build scalable AI solutions integrated with immersive Metaverse environments.

Key Responsibilities

• Define and drive the AI technology vision and roadmap for Metaverse products.
• Lead end-to-end AI product development from concept to deployment.
• Design and implement LLM-powered applications, AI agents, copilots, and intelligent assistants.
• Build scalable RAG architectures integrating vector databases and enterprise knowledge repositories.
• Develop and optimize ML and Deep Learning models for real-world business applications.
• Lead research and implementation of Transformer-based architectures.
• Collaborate with Product, Engineering, UX, BIM, CAD/CAE, Digital Twin, and Metaverse teams.
• Establish AI governance, model evaluation, security, and responsible AI practices.
• Drive cloud-native AI deployments and MLOps practices.
• Mentor and lead high-performing AI engineering and data science teams.

Must-Have Skills

• 6+ years of software engineering and product development experience.
• 3+ years of hands-on experience in Machine Learning and AI product development.
• Prompt Engineering: Utilizing LLMs and generative AI tools to accelerate code writing and data extraction.
• Data Governance: Ensuring AI models follow privacy laws, security protocols, and ethical data guidelines.
• Strong expertise in Generative AI and Large Language Models (OpenAI, Llama, Claude, Gemini, etc.).
• Proven experience designing and implementing RAG-based systems.
• Deep understanding of Transformer architectures and attention mechanisms.
• Strong experience with Deep Learning frameworks such as PyTorch and TensorFlow.
• Experience in NLP, semantic search, embedding, vector databases, and knowledge retrieval.
• Expertise in AI model training, fine-tuning, evaluation, and optimization.
• Strong programming skills in Python and related AI ecosystems.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Experience implementing MLOps, CI/CD, model monitoring, and AI deployment pipelines.
• Strong product ownership and stakeholder management experience.
• Experience leading large engineering teams and delivering enterprise-scale products.

Good-to-Have Skills

• Experience in Metaverse, Digital Twin, XR/VR/AR platforms.
• Exposure to CAD, CAE, BIM, construction technology, or industrial engineering domains.
• Experience building AI agents and autonomous workflows.
• Knowledge of Graph RAG, Knowledge Graphs, and Agentic AI frameworks.
• Experience with multi modal AI models (text, image, video, 3D).
• Exposure to computer vision, 3D scene understanding, and spatial computing.
• Experience with Unity, Unreal Engine, or real-time 3D platforms.
• Understanding of distributed systems and high-performance computing.
• Publications, patents, or contributions in AI research.

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.

Leadership Expectations

• Ability to define AI strategy aligned with business objectives.
• Drive innovation and adoption of emerging AI technologies.
• Build and mentor world‑class AI engineering teams.
• Communicate effectively with executive leadership, clients, and technical teams.

Success Metrics

• Successful delivery of AI-powered Metaverse products.
• Scalable deployment of LLM and RAG-based solutions.
• AI innovation, patents, research contributions, and product impact.
• Team growth, engineering excellence, and customer satisfaction.