Job Profile :

You will play a key role in shaping the end-to-end AI architecture strategy in the Integration and Verification Domain.

You will define scalable, secure, and future ready AI platforms and solution blueprints that support business workloads.

You will collaborate with global engineering, product, IT and business teams to define the AI roadmap, own architectural governance, and ensure successful delivery of AI/ML use cases across the organization.

In this role, you will influence adoption of AI, orchestrate cloud-native AI platforms, drive AI maturity, and leverage state-of-the-art technologies in areas such as GenAI, Machine Learning and Cloud.

Provide technical leadership, mentorship, and guidance to AI engineers, data scientists, and solution architects

What should you bring along?

1. 14+ years of overall IT experience, with at least 5 years in AI/ML architecture
2. Strong experience designing scalable AI/ML and GenAI architectures
3. Proven leadership abilities—capable of driving initiatives, mentoring teams, and influencing stakeholders
4. Strong communication and decision-making skills to present architectural solutions, converting business problems into scalable AI reference architectures
5. Expertise in building cloud-native architectures on AWS/Azure
6. Experience leading AI platform engineering, model training, deployment, and monitoring
7. Strong understanding of distributed systems, microservices, and API ecosystems
8. Ability to collaborate with cross-functional teams
9. Robust communication skills to articulate technology strategy and architectural decisions
10. Deep understanding of AI security, compliance, responsible AI,



and governance standards

Must have technical skill :

1. Deep understanding of GenAI, Machine learning and deep learning
2. Proficiency in Python and core AI, ML libraries and GenAI frameworks.
3. Knowledge of LLMOps and model lifecycle management for large language models
4. Strong expertise in hyperparameter tuning, model optimization, and performance benchmarking for ML and GenAI models
5. Hands-on experience with AI/GenAI orchestration frameworks, including LangChain and LangGraph, for building RAG workflows, agents, and complex orchestration pipelines
6. Practical experience implementing agentic AI systems, using tools such as Microsoft Copilot, n8n, Grow AI, and similar automation/AI agent platforms.
7. Proven experience designing and implementing API-first architectures.
8. Strong knowledge of AWS /Azure AI/ML services.
9. Experience with fullstack development – Java, Angular , Springboot,PostgreSQL.
10. Experience with Kubernetes, Docker, GitOps, and CI/CD platforms
11. Solid experience in architecting AI and ML pipelines
12. Hands-on experience with vector databases, embeddings, and LLM integration
13. Ability to design high-availability, scalable, and cost-optimized AI platform architectures

Good to have technical skills :

1. Familiarity with event-driven architecture (Kafka, Event Hub)
2. Experience with Edge AI and real-time inference workloads
3. Understanding of Zero Trust Architecture for AI workloads
4. Certifications in cloud platforms or AI/ML specializations
5. Experience with open-source LLMs and model optimization techniques
6. Background in enterprise architecture frameworks such as TOGAF or Zachman

📌 Senior Solution Architect (Pune)
🏢 BMW TechWorks
📍 Pune