Experience: 10-15 years

Location: Pune, India

Job Summary
We are looking for a highly experienced Solutions Architect / ML Systems Engineer responsible for owning the end-to-end technical architecture and delivery of complex ML/LLM-based solutions. The role requires strong breadth across application architecture, ML/LLM systems, cloud, infrastructure, performance engineering, security, and enterprise deployments.

Key Responsibilities

- Own the end-to-end technical architecture and solution design for enterprise-grade ML/LLM solutions.
- Design multiple solution architectures based on business, technical, scalability, security, and performance requirements.
- Ability to co-work with Agentic AI model, Optimizing processes agnatically [agentic optimizing engineering].
- Define technical approaches covering application development, infrastructure, deployment, testing, and operational considerations.
- Work closely with customers and engineering teams to understand requirements and translate them into scalable technical solutions.
- Design solutions for both on-premises/data-center and public-cloud environments.
- Architect containerized deployments and cloud-native solutions.
- Define and address non-functional requirements, including performance, scalability, availability, reliability, and security.
- Provide technical ownership across the complete solution lifecycle, from initial architecture through implementation and deployment.
- Evaluate technology choices, architecture patterns, and deployment models.
- Work on performance engineering and performance optimization of ML/LLM systems.
- Ensure appropriate quality standards, testing approaches, KPIs, and engineering practices are incorporated into the solution.




- Support multiple enterprise solution implementations and pilots.
- Must be available for on-call support as needed
- Ability to collaborate effectively with Agentic AI models
- Capability to optimize repetitive processes and workflows using agentic/autonomous engineering approaches

Required Technical Skills

- Strong hands-on experience with ML Systems Engineering / MLOps / LLMOps.
- Practical experience deploying and operating LLM applications at scale.
- Strong understanding of RAG, AI/LLM application architecture, prompt injection, security, guardrails, and observability.
- Experience with LLM infrastructure and supporting technologies.
- Strong understanding of containers, Kubernetes, CI/CD and DevOps practices.
- Experience with public cloud platforms such as AWS, Azure or GCP.
- Understanding of on-premises, cloud, hybrid-cloud and data-center deployments.
- Strong knowledge of performance engineering and non-functional requirements.
- Understanding of enterprise-grade security and deployment considerations.

Preferred / Differentiating Experience

- Experience working on B2B enterprise products/platforms.
- Experience with products supporting both data-center and cloud deployment models.
- Exposure to AI accelerators / AI hardware.
- Experience working with semiconductor/AI platforms or simulation environments.
- Experience designing solutions for enterprise customers.

Soft Skills

- Excellent customer-facing and stakeholder-management skills.
- Strong architectural thinking and problem-solving ability.
- Ability to communicate complex technical concepts to technical and business stakeholders.
- Solid ownership and ability to drive solutions independently.

📌 Technical Project Manager – Enterprise AI (Pune)
🏢 Emergys
📍 Pune