AI Architect

About us:

L&T Technology Services Limited (LTTS) is a global leader in Engineering and R&D (ER&D) services. With 816 patents filed for 57 of the Global Top 100 ER&D spenders, LTTS lives and breathes engineering and technology. Our innovations speak for themselves Worlds 1st Autonomous Welding Robot, Solar Connectivity Drone, and the Smartest Campus in the World, to name a few.

Key Responsibilities:

Enterprise AI Strategy & Governance

1. Develop and implement a scalable AI architecture framework that aligns with enterprise IT strategy and business objectives.
2. Define best practices, design patterns, and reference architectures for AI/ML systems.
3. Establish AI solution governance, including model risk management, lifecycle management, and compliance with responsible AI practices.

Solution Architecture & Design

1. Design secure, scalable AI solutions across multiple business domains (e.g., customer experience, operations, risk, finance).
2. Architect end-to-end ML pipelines: data ingestion, model development, model serving, monitoring, and retraining workflows.
3. Collaborate with infrastructure teams to deploy AI workloads on cloud (AWS/GCP/Azure) or hybrid environments using containers and orchestration tools (Kubernetes, Docker).

Cross-Functional Collaboration

1. Serve as the bridge between data science, software engineering, business stakeholders, and enterprise architects.
2. Translate complex business requirements into AI-driven technical solutions.
3. Drive adoption of enterprise-wide AI tools, platforms, and shared services.

Innovation & Emerging Technologies

1. Evaluate and integrate emerging AI technologies such as generative AI, large language models (LLMs), edge AI, and automated machine learning (AutoML).
2. Lead AI PoCs and pilots, and provide technical thought leadership on AI trends and capabilities.

Mentoring & Leadership

1. Guide and mentor solution architects, data engineers, and data scientists.
2. Present architectural roadmaps and AI strategies to executive leadership and enterprise governance boards.

Required Qualifications:

1. 12+ years in software/data engineering, including 3+ years of AI/ML solution architecture in enterprise environments.
2. Proven experience designing and deploying AI solutions at enterprise scale.
3. Strong technical knowledge of:
4. Machine learning frameworks (TensorFlow, PyTorch, Scikit-learn)
5. MLOps platforms (MLflow, Kubeflow, SageMaker, Vertex AI)
6. LLM Models like Gemini , Open AI
7. MCP, A2A Protocols
8. Big data platforms (Spark, Databricks, Snowflake)
9. Cloud computing (AWS, GCP, Azure)
10. Familiarity with LLMs, natural language processing (NLP), computer vision, or time-series modeling.
11. Strong communication and presentation skills

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Thanks

Team HR